SOME ASPECTS OF BIOLOGY AND FISHERY OF ACANTHOPAGRUS ARABICUS (IWATSUKI, 2013) (FAMILY: SPARIDAE) FROM KARACHI COAST

Thesis submitted to the University of Karachi in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Zoology

BY

SHAGUFTA RIAZ

DEPARTMENT OF ZOOLOGY UNIVERSITY OF KARACHI KARACHI-75270 PAKISTAN 2019

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DEDICATION

To

My Mother

&

My Husband

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BORAD OF ADVANCE STUDIES & RESEARCH University of Karachi

CERTIFICATE

I have gone through the thesis titled “SOME ASPECTS OF BIOLOGY AND FISHERY OF ACANTHOPAGRUS ARABICUS (IWATSUKI, 2013) (FAMILY: SPARIDAE) FROM KARACHI COAST” submitted by Ms. Shagufta Riaz for the awar of Ph.D. degree and certify that to the best of my knowledge it contains no plagiarized material.

Signature & Seal of Supervisor

Name: Prof. Dr. Atiqullah Khan Department: Zoology Email: [email protected] Mobile No: 0300-2482695

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CERTIFICATE

TO WHOM IT MAY CONCERN

It is certified that this thesis titled “SOME ASPECTS OF BIOLOGY AND FISHERY OF ACANTHOPAGRUS ARABICUS (IWATSUKI, 2013) (FAMILY: SPARIDAE) FROM KARACHI COAST” is submitted to the Board of Advance Studies and Research, University of Karachi by Shagufta Riaz. It satisfies the requirements for the approval of the degree of doctor of philosophy (Ph.D.) in Zoology.

Research Supervisor Dr. Muhammad Atiqullah Khan Professor Department of Zoology, University of Karachi.

Co-Supervisor Prof. Dr. Syed Anser Rizvi Professor Department of Zoology, University of Karachi.

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CERTIFICATE

This Thesis by Ms. Shagufta Riaz is accepted in the present form by the Department of Zoology, University of Karachi as satisfying the thesis requirement for the degree of Doctor of Philosophy in Zoology

Internal Examiner______

External Examiner ______

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TABLE OF CONTENT

LIST OF TABLES……………………………………………..……………… x

LIST OF FIGURES………………………………………………………..… xiii

LIST OF PLATES……………………………………………………….…… xviii

LIST OF ABBREVIATIONS……………………………..………………… xix

ACKNOWLEDGMENT ………………………………………………….… xx

ABSTRACT ……………………………………………………………….… xxi

KHULASA (Urdu) ……………………..…………………………………… xxiii

1. INTRODUCTION …………………………………………………………. 1-5

1.1. Fishery ……………………………………………………………... 1

1.2. Distribution ………………………………………………………... 1

1.3. Length weight relationship ………………………………………... 2

1.4. Condition factor …………………………………………………… 2

1.5. Length frequency distribution ……………………………………… 2

1.6. Morphometric analysis …………………………………………….. 3

1.7. Reproductive biology ……………………………………………… 3

1.8. Diet and feeding habits …………………………………………….. 4

1.9. Macro-nutrients and Trace elements ……………………………… 5

1.10. Aims and Objectives …………………………………………….. 5a

2. REVIEW OF LITERATURE ……………………………………….……. 6-17

2.1. Fishery…………………………………………………..………….. 6

2.2. Estimation of Length-weight relationship, Condition Factor (K)……

and Relative Condition Factor (K n)...... … 7

2.3. Length-frequency distribution………………………………………… 9 2.4. Morphometric analysis ……………………………………………….. 9

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2.5. Reproductive biology…………………………………………. ……… 11 2.5.1. Gonado-somatic Index (GSI)……………………………………….. 12 2.5.2. Fecundity……………………………………………….…………… 13 2.5.3. Sex ratio………………………………………………..…………… 13 2.6. Diet of Acanthopagrus arabicus ……………………………………… 14 2.7. Determination of macro-nutrients and trace elements………………… 16 3. MATERIALS AND METHODS...... 18-26 3.1. Study site and duration of study………………………….…………. 18

3.2. Sample preparation and data analysis……………………………….. 18

3.2.1. Measurements …………………………………………………….. 18

3.2.2. Dissection………………………………………………………….. 18

3.2.3. Statistical analysis …………………………………….………….. 18

3.3. Collection of fishery data…………………………………………… 18

3.4. Estimation of Length-weight relationship, Condition Factor (K)……

and Relative Condition Factor (K n)...... ……………….. 21

3.5. Length-frequency distribution………………………………………… 22 3.6. Morphometric analysis ……………………………………………….. 22 3.7. Reproductive biology…………………………………………. ……… 22 3.7.1. Macroscopic analysis…………………………………………..……. 22 3.7.2. Histological analysis……………………………………………….. 23 3.7.3. Gonado-somatic index……………………………………………… 23 3.7.4. Fecundity……………………………………………………………. 23 3.8. Diet of Acanthopagrus arabicus ……………………………………… 23 3.8.1. Sample analysis…………………………………………………….. 23 3.8.2. Food composition…………………………………………………… 24 3.8.3. Index of prepondernace………………………………………...….. 24 3.8.4. Relative gut length (RGL)……………………………………..…… 24 3.8.5. Gastro-somatic index (GaSI)………………………………………. 25 3.9. Determination of macro-nutrients and trace elements………………… 25 3.9.1. Sampling…………………………………………………………………… 25 3.9.2. Sample preparation and chemical analysis ………………………… 25

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3.9.3. Elemental analysis………………………………………………….. 26 3.9.4. Statistical analysis ……………………………………………….... 26 4. RESULTS …………………………………………….…………………. 27-140 4.1. Role of Acanthopagrus Fishery in Pakistan………………………… 27

4.1.1. Fishing gears …………………………………………………….... 27

4.1.2. Catch and landings at Karachi fish Harbor…………………..…… 27

4.1.3. Trends in fish export of Pakistan………………………………….. 29

4.2. Estimation of Length-weight relationship, Condition Factor (K)……

and Relative Condition Factor (K n)...... 32

4.3. Length-frequency distribution…………………………………….… 47

4.4. Morphometric analysis ……………………………………………….. 48 4.5. Reproductive biology…………………………………………. ……… 82 4.5.1. Morphological and histological observations of gonads and hermaphroditism…………………………………………..……. 82 4.5.2. Length at 50 % matuartion………………………..……………… 86 4.5.3. Gonado-somatic Index (GSI) ………………………………….…. 87 4.5.4. Sex ratio…………………………………………………………… 93 4.5.5. Fecundity…………………………………………………………. 96 4.6. Diet of Acanthopagrus arabicus …………………………………… 106 4.6.1. General composition…………………………………………….. 106 4.6.2. Feeding intensity on the basis of different seasons and sizes…….. 108 4.6.3. Seasonal variation in the percentage food composition…………… 112 4.6.4. Percentage composition of food in relation to size of the fish……… 115 4.6.5. Gastro-somatic index (GaSI) and relative gut length (RGL) …….. 118 4.6.6. Index of preponderance…………………………………………… 122 4.7. Estimation of macro-nutrients ……………………………….….… 124 4.8. Estimation of trace elements……………………………………….. 130 5. DISCUSSION……………………………………………………………..… 141 6. CONCLUSION…………………………………………………………….. 7. RECOMMENDATIONS………………………………………………… 8. REFERENCES ………………………………………………………………… 147

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LIST OF TABLES Table 4.2.1. Descriptive statistics and measurements for log transformed length and weight of Acanthopagrus arabicus in different seasons of year 2011... 32

Table 4.2.2. Descriptive statistics and measurements for log transformed length and weight of Acanthopagrus arabicus in different seasons of year 2012.... 33

Table 4.2.3. Descriptive statistics and measurements for log transformed length and weight of Acanthopagrus arabicus in different seasons of year 2013... 34

Table 4.2.4. Regression parameters of log length-weight relationship along with‘t’ test for Acanthopagrus arabicus in different seasons of year 2011...... 36

Table 4.2.5. Regression parameters of log length-weight relationship along with‘t’ test for Acanthopagrus arabicus in different seasons of year 2012...... 37

Table 4.2.6. Regression parameters of log length-weight relationship along with‘t’ test for Acanthopagrus arabicus in different seasons of year 2013...... 38

Table. 4.4.1. Basic statistics of morphometric characters of male, female and combined sexes of Acanthopagrus arabicus ...... 49

Table. 4.4.2. Regression on various morphometric measurements of male, female and combined sexes of Acanthopagrus arabicus ...... 51

Table. 4.5.1. Macroscopic and histological characters of testicular and ovarian zone of Acanthopagrus arabicus in different maturity stages. Stages description and oocytes development followed by Hesp et al., (2004) and Wallace and Selman (1989) respectively...... 85

Table. 4.5.4.1. Sex ratio of Acanthopagrus arabicus in different months of the study period...... 94

Table. 4.5.4.2. Sex ratio of Acanthopagrus arabicus in different size ranges... 95

Table. 4.5.5.1. Mean and standard deviation for gonad weight, number of ova (right and left lobe of the ovary) and fecundity in Acanthopagrus arabicus ...... 97

Table. 4.5.5.2.Regression equation for relationship of fecundity with total length (TL), body weight (B.Wt), gonad weight (G.Wt) and gonadal length right (G.L.R) and left (G.L.L) of Acanthopagrus arabicus ...... 98

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Table. 4.6.2.1. Percent occurrence of food items in the stomach of female Acanthopagrus arabicus during different seasons of the study period...... 108

Table. 4.6.2.2. Percent occurrence of food items in the stomach of male Acanthopagrus arabicus during different seasons of the study period...... 109

Table. 4.6.2.3. Percent occurrence of food items in the stomach of male Acanthopagrus arabicus in different size groups...... 110

Table. 4.6.2.4. Percent occurrence of food items in the stomach of female Acanthopagrus arabicus in different size groups...... 111

Table. 4.6.5.1. Mean and standard deviation for Relative gut length (RLG) of female and male Acanthopagrus arabicus in different size groups...... 121

Table. 4.6.6.1. Index of preponderance of food items on female Acanthopagrus arabicus ...... 123

Table. 4.6.6.2. Index of preponderance of food items on male Acanthopagrus arabicus ...... 123

Table 4.7.1. Concentrations of nutrients (%), average body weight (gm) and average total length (mm) of Acanthopagrus arabicus during different months...... 126

Table 4.7.2a. Descriptive statistics, estimated daily intake (EDI) and daily dietary reference intake (DRI in mg) (NIH, USA, 2017) for meat of Acanthopagrus arabicus ...... 127

Table 4.7.2b. Descriptive statistics, estimated daily intake (EDI) and daily dietary reference intake (DRI in mg) (NIH, USA, 2017) for gills of Acanthopagrus arabicus ...... 127

Table 4.7.3a: Pearson’s correlation between body weight of Acanthopagrus arabicus and the concentration of various macronutrients in meat...... 128

Table 4.7.3b: Pearson’s correlation between body weight of Acanthopagrus arabicus and concentrations of macronutrients in gills...... 129

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LIST OF FIGURES

Fig. 4.1.1. Landing of Acanthopagrus spp. in Sindh from 2000 to 2017...... 28

Fig. 4.1.2. Quantity (in metric tons) of fish exported from Pakistan from 2000 to 2018...... 30

Fig. 4.1.3. Earnings (in million US dollars) by fish export from Pakistan during 2000 to 2018...... 31

Fig. 4.2.1. (1a, 1b, 1c, 1d.) Log Length-weight relationship linear plot for male ( ♂) in different seasons of year 2011...... 39

Fig. 4.2.2. (2a, 2b, 2c, 2d.) Log Length-weight relationship linear plot for female ( ♀) in different seasons of year 2011...... 40

Fig. 4.2.3. (3a, 3b, 3c, 3d .) Log Length-weight relationship linear plot for male ( ♂) in different seasons of year 2012...... 41

Fig. 4.2.4. (4a, 4b, 4c, 4d.)Log Length-weight relationship linear plot for female ( ♀) in different seasons of year 2012...... 42

Fig. 4.2.5. (5a, 5b, 5c, 5d.)Log Length-weight relationship linear plot for male ( ♂) in different seasons of year 2013...... 43

Fig. 4.2.6. (6a, 6b, 6c, 6d.)Log Length-weight relationship linear plot for female ( ♀) in different seasons of year 2013...... 44

Fig. 4.2.7. (7a, 7b, 7c, 7d).Condition factor (K) and relative condition factor (K n) in male and female Acanthopagrus arabicus...... 46

Fig. 4.3.1. Length frequency distribution of Acanthopagrus arabicus ...... 47

Fig. 4.4.1. (a) Frequency distribution of total length in female Acanthopagrus arabicus ...... 52

Fig. 4.4.1. (b) Frequency distribution of standard length in female Acanthopagrus arabicus ...... 53

Fig. 4.4.2. (c) Frequency distribution of body weight in female Acanthopagrus arabicus ...... 54

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Fig. 4.4.2. (d) Frequency distribution of head length in female Acanthopagrus arabicus ...... 55

Fig. 4.4.3. (e) Frequency distribution of snout length in female Acanthopagrus arabicus ...... 56

Fig. 4.4.3. (f) Frequency distribution of body depth in female Acanthopagrus arabicus ...... 57

Fig. 4.4.4. (g) Frequency distribution of body breadth in female Acanthopagrus arabicus ...... 58

Fig. 4.4.4. (h) Frequency distribution of caudal peduncle length in female Acanthopagrus arabicus ...... 59

Fig. 4.4.5. (i) Frequency distribution of fork length in female Acanthopagrus arabicus ...... 60

Fig. 4.4.5. (j) Frequency distribution of eye diameter in female Acanthopagrus arabicus ...... 61

Fig. 4.4.6. (a) Frequency distribution of total length in male Acanthopagrus arabicus ...... 62

Fig. 4.4.6. (b) Frequency distribution of standard length in male Acanthopagrus arabicus ...... 63

Fig. 4.4.7. (c) Frequency distribution of body weight in male Acanthopagrus arabicus ...... 64

Fig. 4.4.7. (d) Frequency distribution of head length in male Acanthopagrus arabicus ...... 65

Fig. 4.4.8. (e) Frequency distribution of snout length in male Acanthopagrus arabicus ...... 66

Fig. 4.4.8. (f) Frequency distribution of body depth in male Acanthopagrus arabicus ...... 67

Fig. 4.4.9. (g) Frequency distribution of body breadth in male Acanthopagrus arabicus ...... 68

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Fig. 4.4.9. (h) Frequency distribution of caudal peduncle length in male Acanthopagrus arabicus ...... 69

Fig. 4.4.10. (i) Frequency distribution of fork length in male Acanthopagrus arabicus ...... 70

Fig. 4.4.10. (j) Frequency distribution of eye diameter in male Acanthopagrus arabicus ...... 71

Fig. 4.4.11. (a) Frequency distribution of total length in combined sexes of Acanthopagrus arabicus ...... 72

Fig. 4.4.11. (b) Frequency distribution of standard length in combined sexes of Acanthopagrus arabicus ...... 73

Fig. 4.4.12. (c) Frequency distribution of body weight in combined sexes of Acanthopagrus arabicus ...... 74

Fig. 4.4.12. (d) Frequency distribution of head length in combined sexes of Acanthopagrus arabicus ...... 75

Fig. 4.4.13. (e) Frequency distribution of snout length in combined sexes of Acanthopagrus arabicus ...... 76

Fig. 4.4.13. (f) Frequency distribution of body depth in combined sexes of Acanthopagrus arabicus ...... 77

Fig. 4.4.14. (g) Frequency distribution of body breadth in combined sexes of Acanthopagrus arabicus ...... 78

Fig. 4.4.14. (h) Frequency distribution of caudal peduncle length in combined sexes of Acanthopagrus arabicus ...... 79

Fig. 4.4.15. (i) Frequency distribution of fork length in combined sexes of Acanthopagrus arabicus ...... 80

Fig. 4.4.15. (j) Frequency distribution of eye diameter in combined sexes of Acanthopagrus arabicus ...... 81

Fig. 4.5.2. Percent maturation in female and male Acanthopagrus arabicus (logistic equation used with 95% confidence interval)...... 86

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Fig. 4.5.3.1. Mean GSI of female, male and combined sexes of Acanthopagrus arabicus in different months of the year 2011...... 88

Fig. 4.5.3.2. Mean GSI of female, male and combined sexes of Acanthopagrus arabicus in different months of the year 2012...... 89

Fig. 4.5.3.3. Mean GSI of female, male and combined sexes of Acanthopagrus arabicus in different months of the year 2013...... 90

Fig. 4.5.3.4.Mean GSI in different size groups of male Acanthopagrus arabicus ...... 91

Fig. 4.5.3.5. Mean GSI in different size groups of female Acanthopagrus arabicus ...... 92

Fig. 4.5.5.1. Relationship between fecundity and total length of Acanthopagrus arabicus ...... 99

Fig. 4.5.5.2.Relationship between fecundity and body weight of Acanthopagrus arabicus ...... 100

Fig. 4.5.5.3. Relationship between fecundity and ovary weight of Acanthopagrus arabicus ...... 101

Fig. 4.5.5.4. Relationship between fecundity and ovary length (right lobe) of Acanthopagrus arabicus ...... 102

Fig. 4.5.5.5. Relationship between fecundity and ovary length (left lobe) of Acanthopagrus arabicus ...... 103

Fig. 4.5.5.6. Number of ova in anterior, middle and posterior parts of the ovary (right lobe) of Acanthopagrus arabicus ...... 104

Fig. 4.5.5.7. Number of ova in anterior, middle and posterior parts of the ovary (left lobe) of Acanthopagrus arabicus ...... 105

Fig. 4.6.3.1. Percent total points of food items in female Acanthopagrus arabicus during different seasons...... 113

Fig. 4.6.3.2. Percent total points of food items in male Acanthopagrus arabicus during different seasons...... 114

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Fig. 4.6.4.1. Variation in percent total points of food items amongst different size groups of female Acanthopagrus arabicus ...... 116

Fig. 4.6.4.2. Variation in percent total points of food items amongst different size groups of male Acanthopagrus arabicus ...... 117

Fig. 4.6.5.1. Gastro-somatic index (GaSI) of female Acanthopagrus arabicus ...... 119

Fig. 4.6.5.2. Gastro-somatic index (GaSI) of male Acanthopagrus arabicus ...... 120

Fig.4.8.1. Concentration of Iron in gills of Acanthopagrus arabicus in different months...... 131

Fig. 4.8.2. Concentration of Iron in meat of Acanthopagrus arabicus in different months...... 132

Fig. 4.8.3. Concentration of Chromium in gills of Acanthopagrus arabicus in different months...... 133

Fig. 4.8.4. Concentration of Chromium in meat of Acanthopagrus arabicus in different months...... 134

Fig. 4.8.5. Concentration of Manganese in gills of Acanthopagrus arabicus in different months...... 135

Fig. 4.8.6. Concentration of Manganese in meat of Acanthopagrus arabicus in different months...... 136

Fig. 4.8.7. Concentration of Zinc in gills of Acanthopagrus arabicus in different months...... 137

Fig. 4.8.8. Concentration of Zinc in meat of Acanthopagrus arabicus in different months...... 138

Fig. 4.8.9. Concentration of Mercury in gills of Acanthopagrus arabicus in different months...... 139

Fig. 4.8.10. Concentration of Mercury in meat of Acanthopagrus arabicus in different months...... 140

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LIST OF PLATES

Plate 1. Site map of study area and distribution of Acanthopagrus arabicus along the different coasts including Karachi Fish Harbor (Karachi coastal area)………. 20

Plate. 2. Histological sections of testicular zone in gonad of Acanthopagrus arabicus . (a) Ovotestes of fish with immature male tissues. (b) Spermatogenesis in the testicular zone of the ovotestes. (c) Ovotestes just prior to spawning period with extensive spermatogenesis. (d) Male at the end of spawning period. sc, spermatocytes; cn, chromatin nucleolar oocytes; sg, spermatogonia; st, spermatids; sp, spermatozoa; ct, connective tissue...... 83

Plate. 3. Histological sections of ovarian zone in gonad of Acanthopagrus arabicus . (a) Ovarian zone in early perinucleolar stage. (b) Ovarian zone in vitellogenic oocytes development stage. (c) Maturing ovarian zone. (d) Ovarian zone with advanced vitellogenic oocytes and hyaline oocytes. vo, vitellogenic oocytes; yg, yolk granules; lv, lipid vesicles...... 84

Plate. 4. Dissected Acanthopagrus arabicus showing gut within body cavity and extracted gorged stomach with its contents...... 107

Plate 5. Preponderance of food items in female and male Acanthopagrus arabicus along with the food items recovered from gut...... 122

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List of Abbreviations

ANOVA Analysis of Covariance

DRI Daily dietary reference intake

EDI Estimated daily intake

FAO Food and Agriculture Organisation

GSI Gonado somatic Index

I Index of preponderance

K Condition factor

Kn Relative condition factor

MFD Marine Fisheries Department

NIH National Institute of Health

PBS Pakistan Bureau of Statistics

SPSS Statistical Package for the Social Sciences

WHO World Health Organisation

WWF World Wildlife Fund

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Acknowledgment

Firstly, I would like to thank “Allah the Praise-Worthy”. My sincere gratitude is to my Supervisor Prof. Dr. Muhammad Atiqullah Khan for his continuous support of my PhD work, for his motivation and for his believe in me. I could not have reckoned having a better Supervisor for my PhD.

Besides my Supervisor, I would like to thank Prof. Dr. Syed Anser Rizvi for his time and involvement in my PhD work, for his suggestions and support. Sincere thanks to all my research colleagues specially Syed Faheem Ahmed for sharing his ideas for research.

Special thanks to Khawaja Khizar Hayat for helping me in sample collections during the study, for his hidden support of my PhD study and for his moral support in my hard times during this study.

I would like to thank Mr. Zafar Imam from Marine Fisheries Department, for his cooperation in providing required information for this work. I would like to thank a number of people from the Pakistan Council of Scientific and Industrial Research (PCSIR), Dr. Khalid Jamil, Dr. Khaula Shirin, Dr. Sofia Khalique Alvi and Mr. Sheraz Shafiq, for their help and support in chemical analysis and lab facilities.

My heartiest gratitude to my family, my parents, my sisters and brothers specially Mrs. Nighat Tahir and Muhammad Zubair without their unconditional love and support I could not have done this work. Last but not least, I would like to thank all my friends, for their support and encouragement. Especially Mrs. Huma Sarfraz Siddiqui, for her help and support, not only in my PhD work but also in my life.

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Abstract

The present study is in truth dependent on the economically important fish Arabian yellow-finned sea bream ‘Acanthopagrus arabicus’, found in Arabian Sea coast of Karachi. Samples of this commercially important fish were collected from January 2011 to December 2013 from West Wharf Fish Harbor. Total of 1400 specimens analyzed to determine fishery and several aspects of biology including length-weight relationship, condition factor, length frequency distribution, morphometric analysis, maturation of gonads (macroscopic and microscopic), hermaphroditism, gonado-somatic index, fecundity, sex ratio, feeding habits. Furthermore, a year data (2015) was collected for the determination of macro-nutrients and trace elements.

Length-weight relationships of male and female showed no significant difference (P < 0.05). Overall negative allometric (b < 3) growth observed in both sexes of Acanthopagrus arabicus with an exception of positive allometry (b > 3) noted in autumn 2012 and 2013 (male) and isometry (b = 3) in spring 2011 (male) and 2012 (male and female). Condition factor (K) showed no significant relationship between gender of the species and values of ‘K’. Relative condition factor (Kn) significantly increased with increase in length of both genders of the species. Length frequency distribution in Acanthopagrus arabicus showed polymodal distribution with modal length range from 216 mm to 232 mm. Analysis of ten morphometric characters showed direct proportion (P < 0.05) between length and other morphometric characters of the fish.

Micro and macroscopic studies of the gonads revealed Acanthopagrus arabicus as a protandrous hermaphrodite with single spawning period. Males and females mature and spawned at almost the same time. Length at 50 % maturity was calculated at 199 mm to 215 mm in male and 216 mm to 232 mm in female. Seasonal variation in Gonado-somatic index suggested that Acanthopagrus arabicus spawned in winter (from November to February). Average fecundity ranged from 307851 to 5494245 eggs in females of size range from 215 mm to 345 mm and body weight from 194 g to 810 g. Relationship between fecundity and total length, body weight, gonad weight and gonad length displayed linear trend with highest coefficient of correlation (0.858) between fecundity and gonad length of the fish.

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Diet composition analysis showed that Acanthopagrus arabicus is a carnivorous fish. It feeds mainly on teleost, arthropods and mollusk. Different trends were observed in male and female feeding intensity in different seasons. Active feeding was noticed prior to spawning period in both sexes. Both male and female Acanthopagrus arabicus fed mostly on teleost group in different seasons. Relative gut length (RGL) showed variation from 1.08 to 1.40 in female and 0.94 to 1.33 in male. The females showed highest index of preponderance for teleost group (38.54%) and amongst the males, highest index of preponderance was observed for arthropods (42.64%).

The estimation of macro-nutrients in available in the meat and gills of Acanthopagrus arabicus revealed good source of calcium, potassium, magnesium and sodium. The concentrations of calcium, potassium and sodium were found with statistically significant difference (P < 0.001) between meat and gills of fish. Concentrations of some other trace elements such as iron, chromium, manganese and zinc were also observed in their meat and gills during different months. Toxic elements such as lead and cadmium were not found in meat and gills of Acanthopagrus arabicus . Mercury was detected in very low concentration. Present work also discussed landing data, export trends (2000-2018) and gear used for catch along with life processes to support fisheries management agencies for possible aquaculture practices and increase in export of this commercially important fish.

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1. INTRODUCTION

1.1. Fishery

All the natural reserves along with fisheries can only be managed appropriately through sustainability of these reserves. Several factors like geographic expansion, water pollution, over exploitation and many others are reason for not so good, in the present world fisheries situation. Endurance of these trends is resulting in rising concern for the fishery resource globally (Pauly, 1984, Watson and Pauly, 2001 and FAO, 2009).

This situation is becoming worst in developing countries because of increase in population, short term socio economic concerns and unreliable employment in general and precisely in Pakistan, deprived quality control and over fishing are the main cause for unsustainability (Akhtar, 2010).

Pakistan’s fishing areas are very rich in marine species with commercial importance. Nonetheless, fisheries sector does not imitate this potential in export, which is stagnant for many years. Pakistan has an estimated seafood and fish industry of 1.2 billion dollars. Out of which only exports are nearly 213 million dollars per annum. There are more than 0.8 million people count on this industry for their living directly or indirectly (Akhtar, 2010).

Consequently, fisheries resources management and its sustainable usage requires information of life history factors like, growth and reproduction of the stocks (Parent and Schriml, 1995, Jennings et al., 1998, Musick, 1999, Marriott et al., 2007, Heupel et al., 2010 and Al-Kiyumi, 2013).

1.2. Distribution

Previously, 29 genera with almost 100 species were represented in family Sparidae (Randall, 1995). Whereas currently it’s represented by 36 genera and 139 species worldwide (Eschmeyer, 2013). Seabreams have importance because of their wide range distribution which is not only suitable for semi industrial and moderate scale fisheries instead also in aquaculture practices (Hanel and Sturmbauer, 2000).

In Pakistan family Sparidae (sea breams) represents 14 species of 8 genera including Acanthopagrus arabicus (Iwatsuki, 2013) which is commercially and

1 economically important fish and recently redistributed in Pakistani waters. Arabian yellow-finned seabream ‘Acanthopagrus arabicus ’ locally termed as ‘Dhandya’ is currently known only from Middle Eastern waters (The Gulf) from Duqum (J. Randall’s collection), southern Oman to Qatar (type locality), and off the coasts of Kuwait (including Iran and Pakistan), to Trivandrum, south-western India (Iwatsuki, 2013). Later on further studies confirmed the presence of Acanthopagrus arabicus in Pakistan (Siddiqui, et al., 2014).

1.3. Length weight relationship

Length weight relationship not only provides growth pattern but also plays important role in fishery resource management. It also helps in estimation of population strength (Beverton and Holt, 1957) and the variation that occurred in expected weight is simply because of changes in condition of the fish during its life cycle (Le Cren, 1951).

1.4. Condition factor

Condition factor is estimated generally to observe and compare the wellness of the fish during its growth. It helps provide growth index and intensity of diet of the fish. (Fagade, 1978) Condition factor could also reveal biological state of a fish, effected by several extrinsic (environmental changes, food) and intrinsic (food in stomach, gonadal development) factors. (Nikosky, 1969)

1.5. Length frequency distribution

Along with above mentioned parameters Length frequency distribution analysis also plays an important role in providing information on age groups (Sparre, 1998) and growth, maturity and production of the fishes for better stock assessment. (Cunha et al., 2007 and Andem, et al., 2013)

1.6. Morphometric analysis

Fish biology requires information regarding proportion of growth of the different body parts to the increase of total length of the fish which can be successfully

2 estimated by morphometric analysis. This analysis is essential for fish taxonomy and stock identification as well (Tandon et al., 1993).Stock identification is an interdisciplinary theme that encompasses the apperception of self-sustaining factors contained by natural populations (Cadrin et al., 2005). For this approach, a basic prerequisite is to consider the complete influence of management acts, together with identification of the stock intricacy of a fish species (Begg et al., 1999). Consequently, for effective fishery resource management, it is vital to know stock structure of the species (Grimes et al., 1987).

So far, a number of methods have been used for stock identification including morphometric and meristic etc. nonetheless, morphometric study is frequently used for presenting stock complexity of the exploited fish species (Murta, 2000 and Turan, 2004), as well as it is an effective tool for appraising discreteness of the similar species (Naeem and Salam, 2005).

Usually, fish exhibit enormous morphological variations within and amongst populations than other vertebrates and are more vulnerable to environmental caused morphological changes. For evaluation of wellbeing and viable differences amongst discrete unit stocks of the similar species, relationship between morphometric and different body parts of fish is beneficial (King, 2007).

1.7. Reproductive biology

Reproductive pattern of any individual usually influenced by its maturation, sex ratio, spawning period and fecundity (Stearns, 1992 and Lambert et al., 2003). Determination of maturity stages according to gonad sizes are helpful in understanding composition of the fish stock. For a wild population of fish, size at 50% maturity plays a key role in harvest management decisions (Roa et al., 1999). Similarly, fecundity is also used for a better understanding of reproductive output of a certain fish stock and in the spawning period the number and size of eggs and its quality provides basis for recruitment in the population of fish (Rickman et al., 2000 and Nichol and Acuna, 2001).

Sparids showed diversity in sexuality or reproductive pattern as both sequential and rudimentary hermaphroditism recorded in family sparidae (Atz, 1964 and Buxton and Garratt, 1990). Sequential or functional hermaphroditism along with reproductive biology reported in Acanthopagrus latus belonging to same genus by several authors like; Abu Hakima (1984), Abol-Munafi and Umeda (1994), Abou-Seedo et al., (2003), Hesp et al.,

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(2004) and Vahabnezhad et al., (2016) but to date, the reproductive biology and diet composition of Acanthopagrus arabicus in Pakistan has not been observed.

1.8. Diet and feeding habits

For an effective management of the species within its ecosystem, information on the diet is of fundamental importance (Duffy and Jackson, 1986, Santos et al., 2001 and Hajisamaea et al., 2003). Data of diet composition of targeted species not only help in fisheries management but also considered as key factor in regulation of fish communities structure (Gerking, 1994).

Many researchers believe study of food items and feeding habits provide help to maintain trophic level stability (Wallace, 1981 and Hartvig, 2011) and indicator for overexploitation of certain species (Polis et al., 2000). Quantity and type of gut contents found in the fish mostly depends on factors like seasonal variation, digestion ratio, food chain and size of the fish. Nonetheless, gut content analysis on seasonal basis provides information of occurrence and quantity of the preferable diet of the fish.

Reported diet of sparids mainly consist of benthic prey and sometimes plants as well (Havelange et al., 1997, Tancioni et al., 2003). Many sparids showed variety in feeding habits being an opportunistic feeder (Sarre et al., 2000, Mariani, et al., 2002, Tancioni et al., 2003) as this type of feeders have support of large mouth opening and canine and molariform teeth assemblage (Gomon et al., 1994).

Along with some other species sparids showed changes in diet pattern i.e. size related changes (Stoner and Livingston, 1984, Booth and Buxton, 1997, Sarre et al., 2000, Tancioni et al., 2003) and seasonal changes (Kallianiotis et al., 2005) but there is scarce data available to suggest such changes in sparids (Dia et al., 2000 and Pallaoro et al., 2004).

Presently, there is hardly any available work on feeding habits and seasonal variation of the diet items in the gut of Acanthopagrus arabicus from Pakistan. Nonetheless, little work is available on related species of the family Sparidae including Vahabnezhad et al., (2016) from Iran provided data on feeding habits of Acanthopagrus latus and Norriss et al., (2002) worked on feeding behaviour of Acanthopagrus butcheri in Western Australia. Likewise, Mehanna et al., (2017) suggested feeding pattern in Acanthopagrus bifasciatus from Egypt and Nip et al., (2003) observed feeding ecology of Acanthopagrus schlegeli (larval & juvenile) in Hong Kong.

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1.9. Macro-nutrients and Trace elements

Aquatic organisms including fish accumulate naturally occurring metals in the aquatic systems (Bury et al., 2003). But additional metals coming from polluting sources can cause harmful effects to fish and other aquatic organisms (Biddinger and Gloss, 1984 and Jarvinen and Ankley, 1999).

However, aquatic organisms including fish contain many essential nutrients/metals as well and its consumption by human can help in prevention of many diseases like heart disease, hypertension and cancer. (Simopolpoulos, 1997). Fish is a significant source of protein for people. It delivers vital fatty acids that decrease the risk of heart ailments and stroke. It also play role to lower cholesterol in blood and contains essential vitamins and minerals (Al-Busaidi et al., 2011) . Macronutrients/elements like Magnesium (Mg), Calcium (Ca), Potassium (K) and Sodium (Na) are one of the body requirements for important biological functions. According to Goldhaber (2003), lack or excess intake of these elements may cause chronic ailments and organ glitches, consequently a well- adjusted uptake of diet including essential amount of these elements is necessary. That’s why present study designed to observe both type of metal accumulation in Acanthopagrus arabicus from Karachi coastal waters of Pakistan.

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1.10. Aims and Objectives

Acanthopagrus arabicus is a commercially important fish of Pakistan. Which is widely consumed locally and exported to many foreign countries. Presently, there is hardly any available work on its fishery, reproductive biology, feeding habits and seasonal variation of the diet items in the gut of Acanthopagrus arabicus from Pakistan. This study was undertaken with following objectives to provide a better understanding of life processes of this species to help provide useful data for fishery management agencies:

• To provide fishery data along with landing and export details for Acanthopagrus arabicus with other sea breams found in Pakistan.

• To estimate growth parameters of Acanthopagrus arabicus i.e. length-weight relationship, condition factor, length frequency distribution and morphometric analysis.

• To observe reproductive pattern including maturation, sex ratio, gonado-somatic index, fecundity and hermaphroditism.

• To investigate seasonal variation in feeding habits of Acanthopagrus arabicus .

• To observe bioavailability of trace elements in different organs of Acanthopagrus arabicus .

• To observe bioavailability of macro-nutrients and provide estimated daily intake for human consumption.

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2. Review of Literature

2.1. Fishery

Recently, Nazir et al., (2015) studied the fisheries economy and its management in Pakistan. They suggested emphasis on stable resource management as well as observed problems in maintaining management policies by Government for regulation of fish industry of Pakistan. Very next year Nazir et al., (2016) also provided information on estimation of economic value for the country by observing Pakistan’s fisheries resources including sea bream.

As several authors are now emphasizing more importance of fisheries management from across the world including Pakistan few reports were previously provided mentioning problems in achieving that goal. Like an interim report from Pakistan Sindh Coastal and Inland Community Development Project (2005) which stated that huge potential of fisheries sector was being missed due to weakness in implantation by institutions that governs and manage fisheries sector in the province (Sindh, Pakistan), which resulted in failure to attain maximum yields from the fisheries sector of Pakistan.

Nonetheless, there was a detailed document (National Policy and Strategy for Fisheries and Aquaculture Development in Pakistan, 2006) presented comprised of several parts. It provided policies and strategies for fisheries management along with implementation plans and also suggested governmental arrangements needed for policy implementation accompanied by legal aspects of the policy.

Pet et al., (1995) from Sri Lanka studied several factors like effort, catch and CpUE (catch per unit of effort) quantitatively and suggested the improvements in precision of fisheries statistics and collection of effort and catch data. Similarly, Bose et al., (2017) discussed enforcement of fisheries legislation in Oman and provided perceived views of local enforcement executives which author found similar to fisherman mostly.

There are a number of studies done on fishery of a single model (specie) to provide data for fisheries management of commercially important species. As Pollock and Williams (1983) assessed the fishery of yellow fin bream in Australia and provided observations on the differences occurred in mean catch per unit effort and total yield during

7 the period of 1945 to 1980 and Lammens et al., (2004) studied the commercial fishery effects on the population of bream in Lake Veluwe (Netherlands) and suggested that evaluation of growth data, size distribution and recruitment of population was important along with fishery to explain the changes in biomass. From Kenya Samoilys et al., (2017) studied fisheries and coral reef fish for a period of 20 years and observed the fishing level sustainability.

2.2. Estimation of Length-weight relationship, Condition Factor

(K) and Relative Condition Factor (K n)

Le Cren (1951) determined length-weight relationship of Perch by using an empirical formulae of type W=aL n. According to observed length-weight relationship, Perch divided into six groups which corresponds with sex, age and maturity. Results showed each group significantly differed from other group but was homogeneous within itself in all seasons. Likewise, many other authors estimated length-weight relationship e.g. Dourado and Davies(1978) stated that length weight data of fishes collected from various locations could use to calculate typical average weights for fishes of specific lengths and Ali (1979) suggested that length-weight relationship of Rouch Rutilus rutilus was indistinguishable up to 20.0 cm, as the size increases large sized fishes were marginally weightier at any given length.

Studies by several authors represented growth pattern estimated by length- weight relationship slope including Khan and Hoda (1997 and 1998) whom determined length-weight relationship of Euryglossa orientalis (Bl. & Schn.) and observed linear relationship, similarly Abbas (2000) estimated length-weight relationship of Anchovy and Mullet and suggested that male of both species were heavier and raised sooner than the females in assessment of the values of regression coefficient b which were suggestively greater than b=3.0 (an ideal slope) while Yilmaz, et.al., (2012) observed length-weight relationship of white bream , Blicca bjoerkna . Studies revealed that differentiation seen in male and female slopes of length-weight relationships in different seasons.

Parallel studies like determination of length-weight relationship of Sardinella longiceps from Omani Coast by Saud (2011) suggested that values of b for whole sample were all equivalent to 3.0. Nonetheless, Khan, et al., (2013) estimated length-weight relationship

8 of Pomadasys maculatum from Pakistan and suggested that this specie showed both symmetric and isometric growth pattern.

Several workers suggested negative allometric growth pattern based on length- weight relationship in different species like Dan-Kishiya (2013) observed it in Tilapia zilli , Tilapia mariae , Oreochromis niloticus , Barbus occidentalis and Barilius loati along with condition factor (K) ranged between 1.06 to 2.02 and Ahmed et al., (2011) reported it in six fish species from six families with differences in condition factor ranges amongst species.

Mortuza and Al-Misned (2015) and Isajlovic et al., (2009) also suggested negative allometric growth in Gagata youssoufi , Clupisoma garua , Ompok bimaculatus , Securicula gora , Parambassis ranga , Rhinomugil corsula out of twelve species studied from Bangladesh and in Coelorinchus caelorhincus from northern and central Adriatic Sea respectively.

In Pakistan, negative allometric growth pattern of sparids observed in Acanthopagrus berda from Karachi coast by Hameed et al., (2013) while Hussain et al., (2010) found that 17 species showed negative allometric growth out of 41 fish species studied from Korangi Phitti Creek area.

Condition factor or well-being of fish studied worldwide as Ayo-Olalusi (2010) observed no significant difference in condition factor of male and female Oreochromis niloticus . Although Kumar and Kiran (2016) from observed difference in relative condition factor of Notopterus notopterus during different seasons.

Similarly, Costa and Araujo (2003) suggested ontogenic, spatial and temporal changes in condition factor of Micropogonias furnieri from Brazil and Santos et al., (1995) observed seasonal variation in condition factor of sea breams from South Portugal and suggested that changes occurred in condition factor showed increase and decrease of weight and volume growth of edible muscles. Bolger and Connolly (1989) surveyed two journals with publications on condition factor constructed on length-weight relationship and analyzed 8 forms of indexes used for measuring condition of fish.

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However, Mozsar et al., (2015) presented a different aspect of study on condition factor as they related it with chemical composition of fish along with other growth parameters. Froese (2006) suggested recommendations for proper use of condition factor, length-weight relationship and relative weight.

Length-weight relationship for several species in a study widely presented by researchers as Dolcic and Kraljevic (1996) provided length-weight relationship for 40 fish species from Eastern Adriatic, Petrakis and Stergion (1995) presented length-weight relationship data for 33 species from Aegean Sea, Hussain and Abdullah (1980) also gave data on length-weight relationship of six fish species from Kuwait, Morato et al., (2001) studied it for 21 fish species and Morris (2005) observed difference between length-weight relationship of 20 marine species from Texas and previous studies on same species.

2.3. Length-frequency distribution

A number of studies has been done in order to observe growth in fish by the help of length frequency distribution analysis such as Mathialagan et al., (2013) from India and Adebiyi (2013) from Nigeria provided observations on length frequency distribution in Cirrhinus reba and Pomadasys jubelini respectively.

Detailed study by Andem et al., (2013) provided length frequency distribution analysis for Chrysichthys nigrodigitatus on both seasonal basis and according to size intervals. Over all, highest length frequency distribution recorded in the month of September and in size range of 40-49 cm amongst rest of the months and size ranges. Similarly, Deepti and Sujatha (2017) analyzed length frequency distribution for skip jack tuna in different months of the study.

2.4. Morphometric analysis

For better understanding of stock identification and management of fishery resources, morphometric study is a useful tool since long period. Strauss and Bookstein (1982) explained principles regarding morphometric analyses. They used truss network to describe character selection for morphometric analysis according to form and land marks. Similarly, Cadrin (2000) discussed variation in different morphometric techniques as well as related it with geometric analyses i.e. biologically interpreted and size and shape

10 explained by the help of multivariate morphometrics. Similar approach by Dwived and Dubey (2013) which emphasized importance of morphometric techniques. They reviewed all recent techniques used in morphometric analysis.

Several research workers done morphometric analysis for different fish populations in different parts of the world such as, Uiblein (1995) studied 17 morphometric characters in two populations of ophidiid species from Red Sea and Costa et al., (2003) presented observations on fragmentation of population of toad fish from Portuguese coast by the help of morphometric analysis. This study suggested that morphometric characters were adequate enough to separate individuals from different six localities of sample collection.

While from Thailand Kosai et al., (2014) studied morphometric characters of Oreochromis niloticus and estimated relationship between growths of these characters and total lengths of the fish. Whereas Vatandonst et al., (2014) from Iran also analyzed 31 morphometric characters in native trout from five different rivers to compare differences amongst population.

From other parts of the world a number of work has been done related to morphometrics including, Doherty and McCarthy (2004) from Ireland, O’Reilly and Horn (2004) from California, Cheng et al., (2005) from China, Turan et al., (2005) from Turkey, Darlina et al., (2011) from Malaysia, Hassanien et al., (2011) from Egypt, Yakubu and Okunsebor (2011) from Nigeria, Cronin-Fine et al., (2013) from North America and Mojekwu and Anumudu (2015) from Nigeria.

Similarly, from Pakistan and its neighboring Countries like India and Bangladesh researchers provided data on morphometrics of different fishes from marine and fresh water. Such as Naeem et al (2011), Jalbani et al., (2014), Safi et al., (2014) and Nasir et al., (2017) from Pakistan, Ujjania and Kohli (2011), Saikia (2012), Brraich and Akhtar (2015), Pazhayamadom et al., (2015), Maji et al., (2016), Singla (2016), Surya et al., (2016) and Arora and Julka (2017) from India and Hossain et al., (2010) and Hossain and Sultana (2016) from Bangladesh.

2.5. Reproductive biology

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Tyler and Sumpter (1996) discussed importance of development process of oocytes in reproductive and fishery biology. They reviewed synchronous and asynchronous spawning patterns in teleost along with the growth of oocytes. Similarly, Toor (1964) explained the importance of spawning pattern in pig-face bream. Observations included maturity, spawning period and age of the fish.

Hughes and Stewart (2006) studied reproductive biology of four different gar fish species from Australia. Study showed spawning period between November and December with the help of GSI peaks and 50% maturation in both male and female also presented. Another study by Belova and Viktorovskaya (2007) presented similar aspects for Cucumaria japonica .

Mahmoud (2009) presented spawning period and gonadal development of two species from two different families. A more enhanced study presented by Nakamura (2013) discussed maturation and gonadal sex differentiation in teleost along with hormones and enzymes involved in these processes.

Reproductive biology studied worldwide by several researchers such as Gordon and Bills (1999), Flammang et al., (2008), Keymaram et al., (2010), Panhwar et al., (2012), Oliveira et al., (2015), Mohammadi –Darestani et al., (2016) and Saeed et al., (2016).

Mitcheson et al., (2008) reviewed the hermaphroditism in teleost. They discussed origin, expression and phylogenetic distribution of hermaphroditism and suggested that independent appearance of hermaphroditism in different fishes could be a response of several biological, environmental conditions, limitations and opportunities. Similarly, Alonso-Fernandez et al., (2011) emphasized importance of histological studies of reproductive biology specially to explain hermaphroditism in species.

Reproductive biology of different species belonged to family sparidae studied by a number of workers like, Abu-Hakima (1984) provided observations on reproductive biology of Acanthopagrus spp . El-Sayed and Abdel-Bary (1993) studied reproductive biology and fecundity in Argyrops spinifer from Qatar. Abol-Munafi and Umeda (1994) presented histological study of gonadal stages of Acanthopagrus latus from Japan. Krug (1998) studied proportion of hermaphrodites in blackspot sea bream. Pajuelo et al., (2006)

12 presented study on red-banded sea bream from family sparidae. They collected it from coast of Canarian archipelago and provided its life history in detail.

Abou-Seedo et al., (2003) also provided histological analysis of mature stages and oocyte development in Acanthopagrus latus from Kuwait. In the same way, Hesp et al., (2004) presented observations on reproductive biology of Acanthopagrus latus from Australia. They concluded Acanthopagrus latus as protandrous hermaphrodite by the help of histological and macroscopic study of the gonads. While, Lee et al., (2008) described ovarian and testicular tissues of protandrous hermaphrodite Acanthopagrus schlegeli in detail. Other studies on species from family sparidae, Acanthopagrus latus , Acanthopagrus schlegeli and sparus sarba (GWO, 2008) and Acanthopagrus schlegeli (Jeong et al., 2010) provided useful information on its reproductive biology.

2.5.1. Gonado-somatic Index (GSI)

Murata et al., (1997) studied maturation of gonads in hybrids of three sea breams. Observations showed gonadosomatic index (GSI) of parents peaked in April with values higher than 8 while values in hybrids did not exceeded 1. While others studied different species to observe spawning period with the help of GSI such as, Offem et al., (2008) provided gonadosomatic index in silver cat fish with spawning season i.e. between April and August and Gundersen et al., (2010) suggested February as spawning month with increased gonadosomatic index in Reinhardtius hippoglossoides . Similarly, Munoz et al., (2010) noted variation in spawning interval and in total number of embryos in every single batch with the help of relationship between numbers of developing oocytes, mass of ovary and gonadosomatic index of the fish.

In 2013, Kadharsha et al., suggested spawning period for Saurida undosquamis as October-December because of greater GSI recorded during this period while, Sun et al., (2013) observed GSI for Thunnus obesus indicating multiple spawning periods with a major spawning season during February to September and Rocha and Gadig (2013) observed little variation in GSI of male but seasonal variation recorded in female Rhinobatos percellens .

French et al., (2014) observed low gonadosomatic index in male of Othos dentex which indicated pair spawning that was unusual in a gonochrist serranid. Similar approach

13 presented by Muncaster et al., (2010), M’Hetli et al., (2011) and Absar et al., (2015) for GSI in Labrus bergylta , Sander lucioperca and Oreochromis niloticus respectively.

2.5.2. Fecundity

Fecundity estimations provide vital information for reproductive and fishery biology. Hence, several workers observed fecundity in different species such as, Juras and Yamaguti (1989) observed variation in fecundity of different sized kin weak fish. Hunter (1992) studied annual fecundity of Dover sole and suggested it has determinate fecundity.

Tyler and Sumpter (1996) reviewed determinants of fecundity in teleost and suggested that usually primary part of gametogenesis initiate determinants of fecundity. While Plaza et al., (2007) found indeterminate fecundity in round herring. Similarly, Mohammad and Pathak (2010) presented fecundity of Labeo rohita and observed relationship of fecundity with ovary weight, ovary length, total length and total weight of the fish. Similar approach adopted by Nandikeswari and Anandan (2013) and Jan et al., (2014) for estimation of fecundity in Terapon puta and Schizothorax plagiostomus respectively. Allison (2011) studied fecundity of Pellonula leonensis and concluded that no seasonal variation observed in fecundity and Hoseinzade et al., (2012) estimated fecundity in Acipenser persicus from Caspian Sea.

2.5.3. Sex Ratio

Most of the studies on reproductive biology included estimation of sex ratio such as, Juras and Yamaguti (1989) provided sex ratio in kin weak fish. Result stated monthly variation in observed sex ratio along with dominance of males. Similarly, Krug (1998) estimated sex ratio in blackspot sea bream.

Il’insky and Kuznetsova (2010) observed yearly variation in sex ratio of notched fin eelpout. While studies on variation in sex ratio between male and female reported by Saud (2011) found female to male sex ratio as 0.6 in Sardinella longiceps from Oman and Agbugui (2013) observed sex ratio in Pomadasys jubelini . Result showed sex ratio of 1:2.1 (male to female).

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Numerous work on sex ratio of different species included, Salmon (Jensen and Hyde, 1971), Snow trout (Mohan, 2005), Rhinomugil corsula (Mortuza and Rahman, 2006), Mystus cavasius (Roy and Hossain, 2006), Pomadasys incises (Fehri-Bedout and Gharbi, 2008), Nile Tilapia (Adel, 2012), Lythrypnus dalli (Kappus, 2012), Oreochromis andersonii (Kefi et al., 2012) and Pomadasys jubelini (Adebiyi, 2013).

Similar work reported from Pakistan included, Khan and Hoda (1993) provided sex ratio of sole, Panhwar et al., (2011) observed sex ratio in Tenualosa ilisha , Mahmood et al., (2011) presented sex ratio of Indian ilisha, Khan et al., (2013) estimated sex ratio of Sillago sihama and Amtyaz et al., (2014) provided sex ratio in Pomadasys maculatum .

2.6. Diet of Acanthopagrus arabicus

There has been several methods used by researchers for gut content analysis and diet composition presentation such as Hynes (1950) assessed different commonly used methods and explained diet items of fishes with general diet. Reid (1961) provided size related differences amongst diet composition of two different Salmon species from Alaska. Lima-Junior and Goitein (2001) explained different methods used in gut content analysis and suggested allocation of points for possible utilization of the methods.

Two different studies by Napazakov (2008), Poltev and Stominok (2008) from Russia presented detailed study of diet items and feeding activity of three different carnivorous species and Gadus macrocephalus ’s dietary composition and its feeding intensity respectively.

Babare et al., (2013) discussed diet of cat fishes and suggested increase in percentage of animal food items in the diet with increase in body size of the fish. Though no habitat related changes observed. Pompei et al., (2014) studied dietary composition and feeding ecology of two species of goby from Italy. Results showed similar diet items found in stomachs of both species with similar feeding habits.

A survey for a period of ten years presented by Il’insky and Kuznetsova (2010) stated food item composition of Zoarces elongatus. A slightly different approach by Karaseva et al., (2013) dealt with presence of eggs and larvae in the diet of Baltic herring

15 and sprat. Similarly, Buckland et al., (2017) suggested condition of prey items influenced gut content analysis as identification of the prey depends upon condition of the stomach.

Many authors discussed seasonal variation in the diet and feeding habits including, Araujo et al., (2005) observed seasonal and spatial changes in Oligosarcus hepsetus ’s diet, Results suggested it has been carnivorous feeder. Similarly, Butler and Wooden (2012) also estimated diet composition of fresh water cod on seasonal basis from Australia. Differences observed in diet items found in fish during summer and winter.

Another study done by Horinouchi et al., (2012) from Thailand presented gut content analysis for 42 species. Food items found in the guts of 13 species showed variation in different seasons. Khan and Hoda (1993) provided observations on diet and feeding habits of Euryglossa orientalis from Pakistan. Diet consisted of annelids, crustaceans and fish etc. and variation amongst food items recorded during different seasons. Similarly Khan et al., (2014) used points and occurrence method for diet composition and feeding habits of Sillago sihama . Results showed fish was carnivorous feeder and diet comprised mainly of mollusks, polychaetes, teleost and echinoderm.

Sparid’s diet observed and discussed by several authors worldwide. Platell et al., (2007) from Australia compared dietary items of Acanthopagrus latus with its size, habitat and seasons. Results stated no size related changes observed however, variation seen in different seasons of the study.

Zakeri et al., (2010) observed effects on growth and spawning of Acanthopagrus latus by artificial diet. Diet with 40 % protein and energy level of 23.5 MJ GE/Kg provided greatest spawning performance.

Vahabnezhad et al., (2016) provided feeding habits of Acanthopagrus latus from Iran. They suggested variations in diet according to size of the fish and in different seasons as well. Diet mainly consisted of mollusks and fish. Another study presented by Sourinejad et al., (2015) proposed Acanthopagrus latus as an omnivorous feeder from Iranian water. Gastrosomatic index indicated high feeding activity during autumn.

2.7. Determination of macro-nutrients and trace elements

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Determination of macro-nutrients and trace elements done worldwide to study its nutritional benefits as well as potential health risks. Several reports has been presented dealing with nutrient composition of fish including macro and micro nutrients such as, FAO/WHO (2011) suggested that fish consumption could help reduce the risk of death by heart disease and improve neurodevelopment in children on mother feed (mother consuming fish during pregnancy). Another report by WHO (1996) provided detailed analysis of trace elements in human nutrition, its source and related health concerns.

Study by Akoto et al., (2014) on metal accumulation in fish and potential health risk by these metals reported high concentration of manganese, iron and zinc and comparatively low concentration of lead, cadmium, chromium, copper and nickel which suggested no significant health risk in consumption of fish containing these metals because of low estimated daily intake. Similar work by Yilmaz et al., (2010) from Turkey provided macro and micro-nutrients analysis and studied possible health risk concerns as well.

Similar reports in Pakistan has been presented such as, report by UNICEF (2001) from Peshawar provided micro-nutrients uptake along with its source in Pakistan and Tariq et al., (1993) also determined 11 trace metals and 4 macro-nutrients in 6 marine edible fish species from Pakistan. They compared observations with previous available data and found higher level of metals in their results.

Several workers observed metal accumulation in sparids from different parts of the world such as, Saei-Dehkor and Fallah (2011) observed metal accumulation in Acanthopagrus latus along with other fishes from Persian Gulf. Study concluded metal concentrations influenced by seasonal variation. Observations on health of Acanthopagrus latus effected by contaminants (metals) recorded by Salamat et al., (2013). They used gill histological changes as a biomarker and indicated difference amongst concentrations in different tissues. In same year i.e. 2013 Yesser and Al-Taee provided observations on frozen, fresh and canned fish including Acanthopagrus latus . Results showed variations in the observed values of trace elements amongst fresh, frozen and canned fishes. Nonetheless, in a previous study by Agusa (2005) on trace elements estimation from different marine fish species, liver and muscles were used for elemental detection.

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Mercury level estimation has been done by several workers in different species of the genus Acanthopagrus such as Chen (2002) recorded high concentration of mercury in muscle and liver of Acanthopagrus berda and P. indicus amongst other fishes, Hedayati et al., (2010) found that mercury was more toxic for Acanthopagrus latus than for other species and study of mercury chloride in serum of Acanthopagrus latus suggested biochemical changes in serum by mercury (Hedayati et al., 2011). Safahieh et al., (2013) also provided study on mercury intake by the consumption of Acanthopagrus latus .

Some other work on metal detection included, Kumar et al., (2012) from India, Sun and Jeng (1998) from Taiwan, Tariq et al., (1998) from Pakistan, Hung et al., (1999) from Taiwan, Saleem et al., (2002) from Pakistan, Shriadah and Emara (1991) from Eqypt, Al-Majed and Preston (2000) from Kuwait, Agusa et al., (2005) from Malaysia, Adams and McMichael (2007) from America, Rejomon et al., (2010) from India, Khoshnood et al., (2012) from Persian Gulf, Chetelat et al., (2013) from Canada, Tyokumbur (2016) from Nigeria and Ahmed et al., (2016) from Pakistan.

3. MATERIALS AND METHODS

3.1. Study site and duration of study

Fresh samples of the Acanthopagrus arabicus (Arabian yellow finned sea bream) found in Arabian Sea were collected monthly from the commercial landings at the Karachi fish harbour (Plate 1), from January 2011 to December 2013.

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3.2. Sample preparation and data analysis

3.2.1. Measurement

A total of 1400 specimens measured for Total Length (TL) from snout to tip of the caudal fin and Body Weight (B.Wt) to nearest 0.1mm and 0.01g respectively before dissection. The digital balance was used to measure body weight.

3.2.2. Dissection

Alimentary canal and gonads were removed to observe their feeding habits, reproductive biology and histological examination in different seasons for the period of three years. Meat and gills were removed from these specimen during the last year of study for evaluation of trace elements, weighed and freeze in tagged envelops for further analysis.

3.2.3. Statistical analysis

Tables and graphs were prepared by using Microsoft Excel (2013). Statistics were performed on the software package SPSS (IBM SPSS version 22 and older versions 17 and 15 as well). Regression illustrated on log transformed data by using least square methods.

3.3. Collection of Fishery data

Detailed review of literature have gone through on fisheries and export of fish and fish products in order to achieve the objective of the present studies. Besides these literatures, some information gathered from the relevant institution as Marine Fisheries Department (MFD) Government of Pakistan approached. Other sources were also used to strengthen present work including, Food and Agriculture Organization (FAO), Pakistan Bureau of Statistics (PBS), World Wildlife Fund (WWF) Pakistan.

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Plate 1. Site map of study area and distribution of Acanthopagrus arabicus along the different coasts including Karachi Fish Harbor (Karachi coastal area).

3.4. Estimation of Length-weight relationship and Condition factor

LWR calculated by using: W= a L b (Le Cren, 1951)

Where, W = Body Weight (g) a = Regression intercept (constant)

L = Total Length (mm) b = Regression slope (constant)

Log transformed data was used.

Linear relationship, standard error and coefficient of correlation were also calculated. ‘t’ test performed and regression coefficients were compared by using analysis of covariance (ANOVA) (Zar, 1999). Scatter diagram was used to show relationship of length and weight in the form of

Y = a+b X (on log transformed data)

Where, Y = log body weight

X = log total length a & b = constant

Condition factor calculated by K = 100aL ᵇ-3 (Clark, 1928), which was derived from Fulton’s condition factor equation by replacing W in K = 100 W/L 3 with aL b because W = aL bas mentioned above. Where W = a = Regression intercept (constant) b = Regression slope (constant) L = Total length (mm) Standard error and coefficient of correlation were also calculated.

21

3.5. Estimation of Length frequency distribution

The sampled data was grouped into size classes of 10 mm interval for later analysis. Demonstration of percent length frequency distribution delivered for size wise data by using a graph representing bar chart for variation of length frequency distribution while month wise data presented in the table for frequencies of male and female during study.

3.6. Morphometric analysis

For each specimen, ten morphometric characters including total length (TL), standard length (SL), body weight (B.Wt.), head length (HL), snout length (Snt.L), body depth (B.Dept.), body breadth (B.Brdth.), caudal peduncle length (C.P.L), fork length (FL), eye diameter (E.Dia.) were measured on the right side of the fish nearest to 0.1 millimetre by using a divider and a measuring scale except for body weight which was measured by using electronic balance. Basic statistical analysis was carried out for all the morphometric characters. Regression for morphometric characters relative to total length (TL) was estimated to find out the relationship between fish size (TL) and allometric coefficients of morphometric characters along with t-test. Graphical representation used for presentation of frequencies of all morphometric character, in female, male and combine data.

3.7. Reproductive Biology

To study the reproductive biology of Acanthopagrus arabicus, gonadal maturity including 50% maturation, sex ratio, gonado-somatic index and fecundity estimated.

3.7.1. Macroscopic analysis

During sample analysis following categories observed in the gonads of Acanthopagrus arabicus :

(i) Thread like, very thin with indeterminate sex found in individuals having total length less than 165 mm.

22

(ii) Ovotestes with predominated ovarian zone.

(iii) Ovotestes with predominated testicular zone.

(iv) Ovaries (> 355 mm) all females.

Each gonad with ovarian/testicular tissue predominance macroscopically analysed and allocated one of the following seven maturity stages derived (with modification) from Laevastu (1965): I = Virgin, II = Immature, III = Developing, IV = Maturing, V = Mature, VI = Spawning and VII = Spent.

3.7.2. Histological analysis

Gonads used to make histological sections for estimation of immature and mature stages in both male and female. For this purpose gonads left in Bouin’s fixative for two days and dehydration process performed by using increasing concentrations of ethanol (i.e. 70% → 95% →100%). Embedding done in Paraffin wax and 5µ thick sections were cut and stained with haematoxylin and eosin.

3.7.3. Gonado-somatic Index (GSI)

After distribution of maturity stages according to gonads both macroscopically and microscopically, 50 % maturation determined amongst maturity stages of male and female along with gonado-somatic index (GSI) for estimation of spawning season of Acanthopagrus arabicus by using formula (June, 1953):

GSI = x 100

3.7.4. Fecundity

For determination of fecundity, 50 ovaries in stage V and VI used from fish belonging to size ranging 216 mm to 345 mm total length during spawning season. Linear regression used to observe relationship of fecundity with total length, body weight, gonad weight and gonad length of the fish.

3.8. Diet of Acanthopagrus arabicus

3.8.1. Sample analysis

23

After dissection length of whole alimentary canal of all individuals were recorded in millimetres (mm) and stomachs were separated from alimentary canal, weighed in gram (g) and length was taken in millimetres (mm) and then stored in 70% ethanol. Each gut was examined and its fullness estimated visually on a scale of 0% (empty) to 100% (gorged). Contents of each gut were viewed under binocular and each dietary item was identified and categorised into three major taxonomic groups i.e. Teleost, Arthropod and Mollusc while, unidentified, semi digested food and animal derivatives were collectively put under group ‘Miscellaneous’.

3.8.2. Food composition

Volumetric method and occurrence method described by Swynnerton and Warthington (1940), reviewed by Hynes (1950) were used in present study with few modification in the allotment of points for fullness of the stomachs i.e. 100, 75, 50, 25, 12, 6 and 0 for gorged, full, ¾ full, ½ full, ¼ full, barely full and empty stomachs respectively.

3.8.3. Index of preponderance

Index of preponderance (Natarajan and Jhingran, 1961) was calculated to find out relative significance of all the diet items by using following formula:

I = x 100 ∑

Where, I = Index of preponderance

Vi = volume percentage

Oi = Occurrence percentage

Σ = summation

3.8.4. Relative gut length (RGL)

Relative gut length (RGL) was also estimated to provide characterization (herbivore, carnivore and omnivore) in the fish of different sizes. RGL was calculated by (Al-Hussani, 1949):

RGL =

24

3.8.5. Gastro-somatic Index (GaSI) To examine the feeding intensity in Acanthopagrus arabicus gastro- somatic index (GaSI) also determined by the help of this formula (Bhatnagar and Karamchandani, 1970):

GaSI = x 100

3.9. Determination of macro-nutrients and trace elements

3.9.1. Sampling

Thirty five fresh sea breams acquired from a native dealer instantly after arrival from the coastal water near Karachi Fish Harbor (source Karachi coast), and elated to laboratory for analysis. All specimens were weighed and total length was also measured. Meat and gills were removed from every individual and weighed. 40 gm of meat and gills from each sample were placed in plastic zip lock bags, tagged and freeze at -21 °C till further analysis.

3.9.2. Sample preparation and Chemical analysis:

For chemical analysis each sample was oven dried at 105 °C till the weight become constant and then homogenized with the help of Pastel mortar. 7 ml of HNO ₃ was then added to each sample and left over night for reaction. Then 1 ml of H₂O₂ added to each sample and kept in microwave digestion system (Anton Paar Multiwave ECO Microwave Digestion System) for 30 minutes at 180°C (800 W). After complete digestion samples were made up with 25 ml volume of distilled water.

However for detection of mercury, oven dried sample were added with 2 ml of sulphuric acid (H2SO 4) and 5-10 ml of nitric acid (HNO 3) and left over night. After which it was covered and heated till complete digestion and make up with 250 ml of H 2O. By

25 using cold vapour technique, 50 ml of digested sample mixed with 8 ml of sulphuric acid

(H 2SO 4) and 8 ml of reducing agent stannous chloride (SnCl 2) (10% solution) and 250 ml of distilled water in reaction vessel.

3.9.3. Elemental analysis:

Hitachi Z-8000 Polarized Zeeman Atomic Absorption Spectrophotometer used for Calcium (Ca), Magnesium (Mg), Potassium (K), Sodium (Na), Iron (Fe), Chromium (Cr), Manganese (Mn) and Zinc (Zn) analysis. While JENWAY Flame photometer used to measure Potassium (K) and Sodium (Na) and for Mercury (Hg) detection, Hitachi Z-5000 Polarized Zeeman Atomic Absorption Spectrophotometer used. Each sample diluted to 10 ppm before run.

3.9.4. Statistical analysis:

Pearson’s Correlation analysis performed by using SPSS 21 (IBM) in order to observe the relationship between Nutrients and fish body weight. Estimated daily intake was calculated by using

EDI = C metal ˟ W/bw (Zhong et al., 2006 and Yu-sheng et al., 2010)

Where, EDI = estimated daily intake

Cmetal = concentration of metals

W = average daily intake of fish bw = body weight

For EDI calculation FAO (Food and Agriculture Organization)’s report (2010) was taken in account showing per person (70 Kg) consumption of average fish amount taken per day in Pakistan is 5 gram. This value was then multiplied by average estimated concentration of each nutrient present in fish.

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4. RESULTS

4.1. Role of Acanthopagrus fishery in Pakistan

4.1.1. Fishing gears

In Pakistan there are variety of vessels used in fishing sector mainly trawlers, gill- netters, long liners, Howra (for fresh trash fish) and Dhonda (gill-netters). Sea breams which are commercially important for Pakistan including Acanthopagrus arabicus , fished by both industrial trawlers and artisanal fishery.

4.1.2. Catch and landings at Karachi fish harbor

Landings in Pakistan show variety of fish and shellfish like Indian salmon, cat fish, mackerel, pomfret, sea breams, shrimp, squids, lobsters, prawn etc. Karachi fish harbor (Sindh) provides 600,000 metric tons of fish annually including more than 200 species of fish with commercial importance. Catch data for sparids of Pakistan is not available specie wise and all the sparids catches from Pakistan are stated under one group termed as ‘sea bream’. According to SMEDA (Small and Medium Enterprise Development Authority, Government of Pakistan) 2005, sea breams were available in peak during October to December. (Nazir et al., 2015)

Data of Acanthopagrus spp . landings for the period 2000 to 2017 presented in figure 4.1.1. Which showed low quantities in early years (2000-2008) nonetheless increased landings can be observed in recent years (2009-2017). Landing data for eighteen years provided in this study represented highest landing of Acanthopagrus spp . in 2015 with 1963 metric tons while lowest landings observed during 2001 and 2007 with 702 metric tons and 711 metric tons respectively.

27

Acanthopagrus spp . Catch in Sindh (Pakistan) 2500

2000

1500

1000 Quantity Quantity in Metric Tons

500

0 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017

Fig. 4.1.1. Landing of Acanthopagrus spp. in Sindh from 2000 to 2017.

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4.1.3. Trends in fish export of Pakistan

The coastline of Pakistan (1050 kilometers) provides fishing area of approximately 300,270 square kilometers. As fish consumption is quite low in Pakistan as compared to rest of the world, majority of marine fish exported to countries like United States of America, Japan, Europe and Middle East contributing almost 71% of the total export of fish from Pakistan. (SMEDA, 2002)

Pakistan fish exports showed mix trends over the years. Figure 4.1.2. showed slow increase in quantity of fish exported from Pakistan during the years. However, drop observed in 2004, 2009 and 2015 and sudden increase in 2017 with quantity of 198,420 metric tons, suggested a good trend in export of fish from Pakistan. Similarly, export earnings from fish export showed increase during 2000 to 2018 (Figure 4.1.3.).

29

250,000

200,000

150,000

100,000 QUANTITY TONS) QUANTITY (METRIC

50,000

0 200020012002200320042005200620072008200920102011201 2201320142015201620172018

Fig. 4.1.2. Quantity (in metric tons) of fish exported from Pakistan from 2000 to 2018.

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500

450

400

350

300

250

200

Export earnings Export(million$)earnings 150

100

50

0 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018

Fig. 4.1.3. Earnings (in million US dollars) by fish export from Pakistan during 2000 to 2018.

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4.2. Estimation of Length-weight relationship and Condition factor

Values of Minimum, Maximum, and Standard Deviation for Total length (mm) and Body weight (g) of male and female in each season {i.e. Autumn (October, November), Winter (December, January, February), Spring (March, April, May), Summer (June, July, August, September)} of three different years provided in Table 4.2.1., 4.2.2 and 4.2.3.

Table 4.2.1. Descriptive statistics and measurements for log transformed length and weight of Acanthopagrus arabicus in different seasons of year 2011.

Year 2011

Total length Body weight Season Gender N Min Max Mean SD Min Max Mean SD

Male 45 2.236 2.548 2.384 0.069 2.000 2.919 2.439 0.209 Autumn Female 40 2.301 2.458 2.380 0.048 2.190 2.623 2.422 0.140

Male 71 2.217 2.486 2.341 0.074 1.954 2.713 2.357 0.203 Winter Female 62 2.217 2.505 2.341 0.066 1.954 2.803 2.343 0.175

Male 46 2.241 2.531 2.352 0.054 1.978 2.912 2.365 0.166 Spring Female 56 2.267 2.544 2.386 0.071 2.121 3.010 2.483 0.213

Male 55 2.267 2.439 2.337 0.045 2.079 2.593 2.341 0.141 Summer Female 72 2.290 2.465 2.354 0.039 2.146 2.628 2.371 0.117

¶ Autumn (October, November), Winter (December, January, February), Spring (March,

April, May), Summer (June, July, August, September), N = number of specimen, SD = standard deviation

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Table 4.2.2. Descriptive statistics and measurements for log transformed length and weight of Acanthopagrus arabicus in different seasons of year 2012.

Year 2012

Total length Body weight Season Gender N Min Max Mean SD Min Max Mean SD

Male 29 2.301 2.547 2.427 0.071 2.176 2.926 2.591 0.242 Autumn Female 31 2.279 2.538 2.382 0.054 2.097 2.908 2.432 0.163

Male 56 2.236 2.498 2.368 0.063 1.954 2.900 2.406 0.196 Winter Female 61 2.238 2.512 2.382 0.061 2.121 2.806 2.443 0.171

Male 46 2.241 2.531 2.352 0.054 1.978 2.912 2.365 0.166 Spring Female 57 2.265 2.549 2.387 0.067 2.121 2.996 2.475 0.203

Male 55 2.267 2.439 2.337 0.045 2.079 2.593 2.341 0.141 Summer Female 62 2.241 2.537 2.369 0.074 2.061 3.000 2.423 0.223

¶ Autumn (October, November), Winter (December, January, February), Spring (March,

April, May), Summer (June, July, August, September), N = number of specimen, SD = standard deviation

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Table 4.2.3. Descriptive statistics and measurements for log transformed length and weight of Acanthopagrus arabicus in different seasons of year 2013.

Year 2013

Total length Body weight Season Gender N Min Max Mean SD Min Max Mean SD

Male 41 2.305 2.549 2.418 0.065 2.228 2.932 2.548 0.211 Autumn Female 40 2.301 2.458 2.380 0.048 2.190 2.623 2.422 0.140

Male 69 2.217 2.496 2.352 0.073 1.978 2.895 2.377 0.208 Winter Female 73 2.223 2.517 2.363 0.070 2.000 2.789 2.383 0.181

Male 61 2.230 2.526 2.344 0.059 2.021 2.898 2.366 0.172 Spring Female 73 2.258 2.549 2.386 0.066 2.161 2.978 2.475 0.188

Male 86 2.265 2.545 2.330 0.050 2.061 2.883 2.332 0.144 Summer Female 72 2.290 2.465 2.354 0.039 2.146 2.628 2.371 0.117

¶ Autumn (October, November), Winter (December, January, February), Spring (March,

April, May), Summer (June, July, August, September), N = number of specimen, SD = standard deviation

34

Presented data for Length-weight relationship in male and female specimens showed variation in different seasons showing isometric, negative and positive allometric growth. Overall, negative allometric growth observed within a season in both sexes. Positive allometry noticed only in autumn 2012 and 2013 (male) and Isometry in spring 2011 (male) and 2012 (male and female). The variation observed during this study may be due to feeding intensity in that particular season or gonadal cycle of the specie.

There was no significant difference noted in the value of ‘b’ between male and female of the same season with a few exceptions. Log Length-weight relationship showed a significant relationship (P < 0.05, Table 4.2.4., 4.2.5 and 4.2.6.).

35

Table 4.2.4. Regression parameters of log length-weight relationship along with‘t’ test for

Acanthopagrus arabicus in different seasons of year 2011.

Year 2011

Regression SE t-test Season Gender N r² P (a) (b) (a) (b) (a) (b)

Male 45 -4.615 2.959 0.236 0.099 0.954 -19.566 29.921 0.000 Autumn Female 40 -4.158 2.765 0.321 0.135 0.917 -12.969 20.529 0.000

Male 71 -3.649 2.566 0.269 0.115 0.878 -13.547 22.306 0.000 Winter Female 62 -3.591 2.535 0.223 0.095 0.922 -16.072 26.569 0.000

Male 46 -4.710 3.008 0.264 0.112 0.942 -17.807 26.755 0.000 Spring Female 56 -4.509 2.931 0.223 0.093 0.948 -20.262 31.435 0.000

Male 55 -4.659 2.995 0.307 0.131 0.908 -15.196 22.834 0.000 Summer Female 72 -4.084 2.742 0.323 0.137 0.851 -12.643 19.987 0.000

¶ Autumn (October, November), Winter (December, January, February), Spring (March,

April, May), Summer (June, July, August, September), N = number of specimen, SE = standard error

36

Table 4.2.5. Regression parameters of log length-weight relationship along with ‘t’ test for Acanthopagrus arabicus in different seasons of year 2012.

Year 2012

Regression SE t-test Season Gender N r² P (a) (b) (a) (b) (a) (b)

Male 29 -5.434 3.307 0.349 0.144 0.952 -15.590 23.034 0.000 Autumn Female 31 -4.660 2.977 0.203 0.085 0.977 -22.901 34.862 0.000

Male 56 -4.453 2.896 0.365 0.154 0.867 -12.193 18.788 0.000 Winter Female 61 -3.921 2.672 0.292 0.122 0.890 -13.450 21.837 0.000

Male 46 -4.710 3.008 0.264 0.112 0.942 -17.807 26.755 0.000 Spring Female 57 -4.696 3.004 0.156 0.066 0.975 -30.019 45.858 0.000

Male 55 -4.659 2.995 0.307 0.131 0.908 -15.196 22.834 0.000 Summer Female 62 -4.555 2.945 0.210 0.089 0.948 -21.662 33.201 0.000

¶ Autumn (October, November), Winter (December, January, February), Spring (March,

April, May), Summer (June, July, August, September), N = number of specimen, SE = standard error

37

Table 4.2.6. Regression parameters of log length-weight relationship along with‘t’ test for

Acanthopagrus arabicus in different seasons of year 2013.

Year 2013

Regression SE t-test Season Gender N r² P (a) (b) (a) (b) (a) (b)

Male 41 -5.086 3.158 0.327 0.135 0.933 -15.562 23.368 0.000 Autumn Female 40 -4.158 2.765 0.321 0.135 0.917 -12.969 20.529 0.000

Male 69 -3.836 2.641 0.297 0.126 0.867 -12.913 20.924 0.000 Winter Female 73 -3.491 2.485 0.211 0.089 0.916 -16.583 27.914 0.000

Male 61 -4.211 2.806 0.237 0.101 0.929 -17.775 27.769 0.000 Spring Female 73 -4.154 2.779 0.165 0.069 0.958 -25.131 40.117 0.000

Male 86 -4.046 2.737 0.247 0.106 0.888 -16.372 25.814 0.000 Summer Female 72 -4.084 2.742 0.323 0.137 0.851 -12.643 19.987 0.000

¶ Autumn (October, November), Winter (December, January, February), Spring (March,

April, May), Summer (June, July, August, September), N = number of specimen, SE = standard error

38

Regression line plot for male and female in different seasons presented in Figure 4.2.1. (1a, 1b, 1c, 1d), Figure 4.2.2. (2a, 2b, 2c, 2d), Figure 4.2.3. (3a, 3b, 3c, 3d), Figure 4.2.4. (4a, 4b, 4c, 4d), Figure 4.2.5. (5a, 5b, 5c, 5d) and Figure 4.2.6. (6a, 6b, 6c, 6d), which shows a straight line in increasing pattern between log length and log weight of the fish.

Fig. 4.2.1. (1a, 1b, 1c, 1d.) Log Length-weight relationship linear plot for male ( ♂) in different seasons of year 2011.

39

Fig. 4.2.2. (2a, 2b, 2c, 2d.) Log Length-weight relationship linear plot for female ( ♀) in different seasons of year 2011.

40

Fig. 4.2.3. (3a, 3b, 3c, 3d.) Log Length-weight relationship linear plot for male ( ♂) in different seasons of year 2012.

41

Fig. 4.2.4. (4a, 4b, 4c, 4d.) Log Length-weight relationship linear plot for female ( ♀) in different seasons of year 2012.

42

Fig. 4.2.5. (5a, 5b, 5c, 5d.) Log Length-weight relationship linear plot for male ( ♂) in different seasons of year 2013.

43

Fig. 4.2.6. (6a, 6b, 6c, 6d.) Log Length-weight relationship linear plot for female ( ♀) in different seasons of year 2013.

44

Current work suggested no significant relationship between condition factor (K) and the gender of the species; the value of ‘K’ for male and female was more than 1 which indicates good condition of the fish. A slight variation noticed in the value of ‘K’ in different length groups. While relative condition factor (Kn) significantly increased with increase in the length of both genders of the species in Figure 4.2.7. (7a, 7b, 7c, 7d).

45

Fig. 4.2.7. (7a, 7b, 7c, 7d). Condition factor (K) and relative condition factor (K n) in male and female Acanthopagrus arabicus.

46

4.3. Length frequency distribution

Figure 4.3.1 presented length frequency distribution of Acanthopagrus arabicus for the period of three years. In this study, the total length of Acanthopagrus arabicus ranged from 165 mm to 354 mm. Result suggested polymodal distribution in this fish and the modal length range was 216 mm to 232 mm. Highest frequency recorded in entire data was 20.92% in size range 216 mm to 232 mm. An increase in length frequency distribution seen with increase in length of the fish in early stage of growth.

Fig. 4.3.1. Length frequency distribution of Acanthopagrus arabicus .

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4.4. Morphometric analysis

Morphometric measurements including total length (T.L), standard length (S.L), body weight (B.Wt), head length (H.L), snout length (Snt.L), body depth (B.Dept.), body breadth (B.Brdth.), caudal peduncle length (Cd.P.L), fork length (F.L) and eye diameter (E.Dia.) were taken for basic statistical analysis e.g. mean, standard error of mean, standard deviation, variance, skewness and kurtosis (Table. 4.4.1). Result showed female Acanthopagrus arabicus longer (mean T.L 237.78) and heavier (mean B.Wt 290.07) than male (mean T.L 228.25 and mean B.Wt 270.38).

48

Table. 4.4.1. Basic statistics of morphometric characters of male, female and combined sexes of Acanthopagrus arabicus .

Gender Statistics T.L S.L B.Wt. H.L Snt.L B.Dept. B.Brdth. Cd.P.L F.L E.Dia. Mean 228.253 184.073 270.383 57.352 22.021 87.104 32.014 30.994 204.382 14.937 S.E of Mean 1.396 1.258 5.663 0.378 0.159 0.546 0.201 0.211 1.356 0.061 S.D 36.898 33.257 149.727 9.994 4.192 14.436 5.307 5.578 35.839 1.614 Male Variance 1361.476 1106.045 22418.111 99.876 17.574 208.409 28.166 31.115 1284.420 2.606 N=699 Skewness 1.100 1.426 2.204 1.239 1.189 0.995 0.538 0.703 1.295 1.180 S.E of Skewness 0.092 0.092 0.092 0.092 0.092 0.092 0.092 0.092 0.092 0.092 Kurtosis 1.446 2.425 5.214 1.745 2.015 1.114 0.354 0.781 2.087 2.518 S.E of Kurtosis 0.185 0.185 0.185 0.185 0.185 0.185 0.185 0.185 0.185 0.185 Mean 237.782 190.100 290.073 59.437 23.003 89.869 33.562 32.121 213.087 15.340 S.E of Mean 1.361 1.150 5.714 0.385 0.167 0.595 0.212 0.203 1.251 0.060 S.D 36.029 30.449 151.294 10.188 4.424 15.760 5.604 5.386 33.127 1.576 Female Variance 1298.065 927.116 22890.013 103.786 19.574 248.363 31.409 29.004 1097.365 2.485 N=701 Skewness 0.910 1.035 2.390 1.201 1.360 1.523 1.302 1.237 0.693 0.805 S.E of Skewness 0.092 0.092 0.092 0.092 0.092 0.092 0.092 0.092 0.092 0.092 Kurtosis 0.982 1.517 6.777 1.926 2.828 3.229 2.807 2.564 0.574 1.263 S.E of Kurtosis 0.184 0.184 0.184 0.184 0.184 0.184 0.184 0.184 0.184 0.184 Mean 233.024 187.091 280.242 58.396 22.513 88.489 32.789 31.559 208.741 15.139 S.E of Mean 0.983 0.856 4.030 0.271 0.116 0.405 0.147 0.147 0.929 0.043 S.D 36.763 32.013 150.782 10.141 4.336 15.171 5.511 5.509 34.769 1.608 Combine Variance 1351.489 1024.813 22735.193 102.848 18.803 230.163 30.368 30.354 1208.866 2.584 N=1400 Skewness 0.973 1.217 2.284 1.205 1.275 1.303 0.946 0.930 0.977 0.966 S.E of Skewness 0.065 0.065 0.065 0.065 0.065 0.065 0.065 0.065 0.065 0.065 Kurtosis 1.111 1.907 5.971 1.798 2.489 2.500 1.901 1.661 1.214 1.742 S.E of Kurtosis 0.131 0.131 0.131 0.131 0.131 0.131 0.131 0.131 0.131 0.131

* T.L=Total Length,S.L=Standard Length, B.Wt=Body Weight, H.L=Head Length, Snt.L=Snout Length, B.Dept.=Body Depth, B.Brdth=Body Breadth, C.P.L=Caudal peduncle Length, F.L=Fork Length, E.Dia=Eye Diameter, S.E= Standard Error, S.D=Standard Deviation, N=Number 49

Table. 4.4.2 indicated highly significant values (P<0.05) of the relationship between total length and rest of the morphometric characters (standard length, body weight, head length, snout length, body depth, body breadth, caudal peduncle length, fork length and eye diameter) in male, female and combined sexes by the help of regression.

Highest values of correlation coefficient (r 2) observed amongst relationship between total length and standard length, body weight, head length and fork length. Result suggested direct proportion between these characters. While, moderate correlation observed in snout length, body depth, body breadth, caudal peduncle length and eye diameter.

Frequencies of morphometric characters presented in male {Figure 4.4.6 (a), 4.4.6 (b), 4.4.7 (c), 4.4.7 (d), 4.4.8 (e), 4.4.8 (f), 4.4.9 (g), 4.4.9 (h), 4.4.10 (i) and 4.4.10 (j)}in female {Figure 4.4.1 (a), 4.4.1 (b), 4.4.2 (c), 4.4.2 (d), 4.4.3 (e), 4.4.3 (f), 4.4.4 (g), 4.4.4 (h), 4.4.5 (i) and 4.4.5 (j)} and in combined sexes {Figure 4.4.11 (a), 4.4.11 (b), 4.4.12 (c), 4.4.12 (d), 4.4.13 (e), 4.4.13 (f), 4.4.14 (g), 4.4.14 (h), 4.4.15 (i) and 4.4.15 (j)} of Acanthopagrus arabicus with standard deviation and mean.

50

Table. 4.4.2. Regression on various morphometric measurements of male, female and combined sexes of Acanthopagrus arabicus .

S.E S.E t-test t-test Gender Reg. Eq. r² P (a) (b) (a) (b) S.L=0.251 L 1.067 0.019 0.008 -12.919 129.199 0.960 0.000 B.Wt-=4.186L 2.792 0.079 0.033 -53.131 83.415 0.909 0.000 H.L=-0.641L 1.017 0.028 0.012 -22.909 85.574 0.913 0.000 Snt.L=-1.188L 1.072 0.042 0.018 -28.407 60.380 0.840 0.000 Male B.Dept.=-0.158L 0.889 0.047 0.020 -3.380 44.755 0.742 0.000 B.Brdth.=-0.640L 0.909 0.050 0.021 -12.685 42.412 0.721 0.000 Cd.P.L=-0.821L 0.980 0.054 0.023 -15.265 42.871 0.725 0.000 F.L=-0.130L 1.035 0.024 0.010 -5.452 101.863 0.937 0.000 E.Dia.=-0.199L 0.582 0.031 0.013 -6.483 44.756 0.742 0.000 S.L=-0.153L 1.023 0.021 0.009 -7.392 117.155 0.952 0.000 B.Wt=-4.099L 2.749 0.069 0.029 -59.326 94.395 0.927 0.000 H.L=-0.754L 1.063 0.028 0.012 -27.082 90.636 0.922 0.000 Snt.L=-1.328L 1.131 0.043 0.018 -30.558 61.741 0.845 0.000 Female B.Dept.=-0.403L 0.991 0.045 0.019 -8.994 52.514 0.798 0.000 B.Brdth.=-0.697L 0.935 0.048 0.020 -14.455 45.984 0.752 0.000 Cd.P.L=-0.732L 0.942 0.049 0.021 -14.982 45.719 0.749 0.000 F.L=-0.073L 1.011 0.023 0.010 -3.224 105.336 0.941 0.001 E.Dia.=-0.218L 0.591 0.032 0.013 -6.909 44.469 0.739 0.000 S.L= -.195 L 1.042 0.014 0.006 -13.678 173.014 0.955 0.000 B.Wt=-4.110L 2.757 0.052 0.022 -78.322 124.143 0.917 0.000 H.L=-0.686L 1.036 0.020 0.008 -34.911 124.531 0.917 0.000 Snt.L=-1.251L 1.099 0.030 0.013 -41.881 86.938 0.844 0.000 Combine B.Dept.=-0.264L 0.933 0.032 0.014 -8.179 68.316 0.770 0.000 B.Brdth.=-0.677L 0.926 0.035 0.015 -19.541 63.137 0.740 0.000 Cd.P.L=-0.777L 0.961 0.036 0.015 -21.527 62.923 0.739 0.000 F.L=-0.104L 1.024 0.016 0.007 -6.369 147.724 0.940 0.000 E.Dia.=-0.210L 0.588 0.022 0.009 -9.667 63.862 0.745 0.000 *T.L=Total Length,S.L=Standard Length, B.Wt=Body Weight, H.L=Head Length, Snt.L=Snout Length, B.Dept.=Body Depth, B.Brdth=Body Breadth, C.P.L=Caudal peduncle Length, F.L=Fork Length, E.Dia=Eye Diameter, S.E= Standard Error.

51

Fig. 4.4.1. (a) Frequency distribution of total length in female Acanthopagrus arabicus .

52

Fig. 4.4.1. (b) Frequency distribution of standard length in female Acanthopagrus arabicus .

53

Fig. 4.4.2. (c) Frequency distribution of body weight in female Acanthopagrus arabicus .

54

Fig. 4.4.2. (d) Frequency distribution of head length in female Acanthopagrus arabicus .

55

Fig. 4.4.3. (e) Frequency distribution of snout length in female Acanthopagrus arabicus .

56

Fig. 4.4.3. (f) Frequency distribution of body depth in female Acanthopagrus arabicus .

57

Fig. 4.4.4. (g) Frequency distribution of body breadth in female Acanthopagrus arabicus .

58

Fig. 4.4.4. (h) Frequency distribution of caudal peduncle length in female Acanthopagrus arabicus .

59

Fig. 4.4.5. (i) Frequency distribution of fork length in female Acanthopagrus arabicus .

60

Fig. 4.4.5. (j) Frequency distribution of eye diameter in female Acanthopagrus arabicus .

61

Fig. 4.4.6. (a) Frequency distribution of total length in male Acanthopagrus arabicus .

62

Fig. 4.4.6. (b) Frequency distribution of standard length in male Acanthopagrus arabicus .

63

Fig. 4.4.7. (c) Frequency distribution of body weight in male Acanthopagrus arabicus .

64

Fig. 4.4.7. (d) Frequency distribution of head length in male Acanthopagrus arabicus .

65

Fig. 4.4.8. (e) Frequency distribution of snout length in male Acanthopagrus arabicus .

66

Fig. 4.4.8. (f) Frequency distribution of body depth in male Acanthopagrus arabicus .

67

Fig. 4.4.9. (g) Frequency distribution of body breadth in male Acanthopagrus arabicus .

68

Fig. 4.4.9. (h) Frequency distribution of caudal peduncle length in male Acanthopagrus arabicus .

69

Fig. 4.4.10. (i) Frequency distribution of fork length in male Acanthopagrus arabicus .

70

Fig. 4.4.10. (j) Frequency distribution of eye diameter in male Acanthopagrus arabicus .

71

Fig. 4.4.11. (a) Frequency distribution of total length in combined sexes of Acanthopagrus arabicus .

72

Fig. 4.4.11. (b) Frequency distribution of standard length in combined sexes of Acanthopagrus arabicus .

73

Fig. 4.4.12. (c) Frequency distribution of body weight in combined sexes of Acanthopagrus arabicus .

74

Fig. 4.4.12. (d) Frequency distribution of head length in combined sexes of Acanthopagrus arabicus .

75

Fig. 4.4.13. (e) Frequency distribution of snout length in combined sexes of Acanthopagrus arabicus .

76

Fig. 4.4.13. (f) Frequency distribution of body depth in combined sexes of Acanthopagrus arabicus .

77

Fig. 4.4.14. (g) Frequency distribution of body breadth in combined sexes of Acanthopagrus arabicus .

78

Fig. 4.4.14. (h) Frequency distribution of caudal peduncle length in combined sexes of Acanthopagrus arabicus .

79

Fig. 4.4.15. (i) Frequency distribution of fork length in combined sexes of Acanthopagrus arabicus .

80

Fig. 4.4.15. (j) Frequency distribution of eye diameter in combined sexes of Acanthopagrus arabicus .

81

4.5. Reproductive biology

4.5.1. Morphological and histological observations of gonads and hermaphroditism

Paired gonad of Acanthopagrus arabicus suspended by a thin mesochium from the dorsal side of the peritoneal cavity. Posteriorly, fused to form oviduct while free anteriorly. Both lobes usually of equal length, cylindrical with smooth texture. Fish with length of >165 mm contained identifiable testicular and ovarian tissues.

Male considered in present study possess white/translucent flattened gonad contained spermatogonia, spermatocytes and spermatids in crypts (165 mm-198 mm). Prior to spawning period testicular part of the gonad become lobular, white and larger than ovarian zone with early stages of spermatogenesis.(Plate 2).

Spermatozoa released by these males during spawning season as crypts break down. Though gonads of these males contained smaller amount of immature ovarian tissues. After spawning period, testicular zone decreased and equal to ovarian zone. Degeneration of testicular tissues observed and prior to spawning period such ovotestes contained developing oocyte stages.

82

Plate. 2. Histological sections of testicular zone in gonad of Acanthopagrus arabicus . (a) Ovotestes of fish with immature male tissues. (b) Spermatogenesis in the testicular zone of the ovotestes. (c) Ovotestes just prior to spawning period with extensive spermatogenesis. (d) Male at the end of spawning period. sc, spermatocytes; cn, chromatin nucleolar oocytes; sg, spermatogonia; st, spermatids; sp, spermatozoa; ct, connective tissue.

83

Microscopic oocyte development observed in ovaries of Acanthopagrus arabicus from early perinucleolar stage to the mature ovary with advanced vitellogenic oocytes and hyaline oocytes presented in Plate. 3. In early development showed oogonia in stage I similarly, perinucleolar stage oocytes and vitellogenic oocyte observed in developing ovary. While in maturing female yolk granules observed in early vitellogenic oocytes and larger vitellogenic oocytes and hyaline oocytes observed in matured ovaries. Decrease in size and volume of ovary observed in spent fish with presence of atretic follicles. While maturity stages on the basis of macroscopic and microscopic analysis provided in Table. 4.5.1.

Plate. 3. Histological sections of ovarian zone in gonad of Acanthopagrus arabicus . (a) Ovarian zone in early perinucleolar stage. (b) Ovarian zone in vitellogenic oocytes development stage. (c) Maturing ovarian zone. (d) Ovarian zone with advanced vitellogenic oocytes and hyaline oocytes. vo, vitellogenic oocytes; yg, yolk granules; lv, lipid vesicles.

84

Table. 4.5.1. Macroscopic and histological characters of testicular and ovarian zone of Acanthopagrus arabicus in different maturity stages. Stages description and oocytes development followed by Hesp et al., (2004) and Wallace and Selman (1989) respectively.

Stages Macroscopic characters Histological characters

Testis Ovary I. Virgin Small and translucent Small and translucent, Early perinucleolar in appearance. light yellowish in oocytes. color II. Immature Slightly larger than Yellowish orange in Previtellogenic, stage I and pale. color, oocytes perinucleolar oocytes invisible to naked eye. observed, oogonia started to appear. III. Developing Whitish and Slightly larger than Vitellogenic oocyte translucent stage II, reddish in stage. color. IV. Maturing Cylindrical shaped, Larger than stage III, Abundance of yolk creamy white in color reddish orange in granules and vitellogenic occupying 1/2 of color occupying 1/2 of oocytes. body cavity. body cavity. V/VI. Soft and white, Very large, yellowish Oocyte maturation and Mature/Spawning occupying 2/3 of orange, occupying 2/3 hydration occurred. Post body cavity. of body cavity. ovulatory follicles Visible hydrated observed in spawning oocytes in stage VI. ovaries. VII. Spent Flabby, small and Flabby and smaller Atretic vitellogenic slightly reddish in than stage V and VI. oocytes observed. color.

85

4.5.2. Length at 50% maturation

Length at which 50% maturation observed in both male and female Acanthopagrus arabicus presented in Figure 4.5.2. In male, length at 50% maturation observed in size range 199 mm to 215 mm while in female size range of 216 mm to 232 mm. Observation suggested female Acanthopagrus arabicus were larger in size when attained 50 % maturity.

Female Cumulative Maturation % Male Cumulative Maturation %

100.000

90.000

80.000

70.000

60.000

50.000

40.000 % Maturation % 30.000

20.000

10.000

0.000

Fig. 4.5.2. Percent maturation in female and male Acanthopagrus arabicus (logistic equation used with 95% confidence interval).

86

4.5.3. Gonadosomatic Index (GSI)

Monthly variation recorded in mean gonadosomatic index values of male female Acanthopagrus arabicus . Highest values of gonadosomatic index in both male and female observed in winter-spring (November, December, January and February) during the different years of study. Result suggested spawning period of Acanthopagrus arabicus started in winter till beginning of spring with peaks during November (2011 and 2013), December (2012) and January (2011, 2012 and 2013) nonetheless low values of gonadosomatic index observed during rest of the year in male, female and combined sexes (Figure 4.5.3.1, 4.5.3.2 and 4.5.3.3).

Observations on gonadosomatic index in different size groups of male and female Acanthopagrus arabicus provided in Figure 4.5.3.4 and 4.5.3.5. Increased values of gonadosomatic index observed with increase in size of the male and female Acanthopagrus arabicus except in post spawning individuals. First peak observed in size range of 199-215 mm in male and 216-232 mm in female while, second peak noticed in size range of 250-266 mm in male and 267-283 mm in female.

87

Fig. 4.5.3.1. Mean GSI of female, male and combined sexes of Acanthopagrus arabicus in different months of the year 2011.

88

Fig. 4.5.3.2. Mean GSI of female, male and combined sexes of Acanthopagrus arabicus in different months of the year 2012.

89

Fig. 4.5.3.3. Mean GSI of female, male and combined sexes of Acanthopagrus arabicus in different months of the year 2013.

90

Fig. 4.5.3.4.Mean GSI in different size groups of male Acanthopagrus arabicus .

91

Fig. 4.5.3.5. Mean GSI in different size groups of female Acanthopagrus arabicus .

92

4.5.4. Sex ratio

Present study suggested that standard ratio of 1:1 for male to female, examined by Chi- square test (p < 0.05) applied on Acanthopagrus arabicus . Sex ratio along with chi-square during different months of the study period presented in Table 4.5.4.1. High frequency of female than male recorded in spawning months i.e. January and November.

Observation on size wise proportion of male and female presented in Table 4.5.4.2 along with chi-square test. Higher male frequency observed in small size immature fish (182 mm to 198 mm) and higher female frequency observed in larger size mature fish (318 mm to 334 mm). Otherwise, overall frequency of male and female in different months and size ranges showed variation in this study.

93

Table. 4.5.4.1. Sex ratio of Acanthopagrus arabicus in different months of the study period.

Frequency Proportion of Year Month Chi-Square Female Male Male January 25 25 0.50 -- February 18 23 0.56 0.61 March 19 23 0.55 0.38 April 20 20 0.50 -- May 17 16 0.48 0.03 June 19 20 0.51 0.03 July 12 20 0.63 2.00 2011 2011 August 20 21 0.51 0.02 September 21 20 0.49 0.02 October 19 22 0.54 0.22 November 21 23 0.52 0.09 December 19 23 0.55 0.38 January 23 15 0.39 1.68 February 20 21 0.51 0.02 March 15 13 0.46 0.14 April 22 18 0.45 0.40 May 20 15 0.43 0.71 June 18 20 0.53 0.11 July 15 12 0.44 0.33 2012 2012 August 14 11 0.44 0.36 September 15 12 0.44 0.33 October 15 13 0.46 0.14 November 16 16 0.50 -- December 18 20 0.53 0.11 January 24 21 0.47 0.20 February 24 22 0.48 0.09 March 23 21 0.48 0.09 April 25 25 0.50 -- May 25 15 0.38 2.50 June 17 23 0.58 0.90 July 13 21 0.62 1.88 2013 2013 August 21 21 0.50 -- September 17 21 0.55 0.42 October 20 20 0.50 -- November 26 21 0.45 0.53 December 25 26 0.51 0.02

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Table. 4.5.4.2. Sex ratio of Acanthopagrus arabicus in different size ranges.

Size range Frequency Proportion of male Chi-Square (mm) Female Male 165-181 21 36 0.63 3.95 182-198 47 125 0.73 35.37 199-215 133 117 0.47 1.02 216-232 145 147 0.50 0.01 233-249 138 119 0.46 1.40 250-266 103 67 0.39 7.62 267-283 40 31 0.44 1.14 284-300 26 15 0.37 2.95 301-317 13 17 0.57 0.53 318-334 18 10 0.36 2.29 335-354 17 15 0.47 0.13

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4.5.5. Fecundity

Fecundity of Acanthopagrus arabicus ranged from 307851 to 5494245 eggs in female of size range from 215 mm to 345 mm (total length) and with body weight from 194 g to 810 g. Mean and standard deviation for gonad weight, number of ova in left and right lobe of ovary and fecundity presented in Table 4.5.5.1. Highest mean fecundity observed in size range 327 mm to 345 mm with gonad mean weight of 29.50.

Regression showed highest coefficient of correlation between fecundity and gonad length (0.858) (Table 4.5.5.2). Relationship between fecundity and total length (Figure 4.5.5.1), body weight (Figure 4.5.5.2), gonad weight (Figure 4.5.5.3), gonad length right (Figure 4.5.5.4) and left (Figure 4.5.5.5) of the Acanthopagrus arabicus presented in this study. Linear relationship showed increase in fecundity with increase of total length, body weight, gonad weight and length with significant coefficient of correlation. Present study also observed variation in number of ova found in anterior, middle and posterior parts of the right lobe (Figure 4.5.5.6) and left lobe (Figure 4.5.5.7) of the ovary.

96

Table. 4.5.5.1. Mean and standard deviation for gonad weight, number of ova (right and left lobe of the ovary) and fecundity in Acanthopagrus arabicus .

Size Gonad Freq No. of ova (right lobe) No. of ova (left lobe) Fecundity (mm) weight 216-231 10 9.60 ± 1.43 357300.70 ± 227514.60 336376.60 ± 239902.51 63677.30 ± 461752.85 232-247 12 12.75 ± 3.77 1225984 ± 170380.75 1011188.90 ± 187136.72 2237172.92 ± 336501.19 248-262 9 15.33 ± 2.18 1685143.67 ± 186427.72 1428166.89 ± 237387.44 3113310.56 ± 391776.93 263-278 10 20.40 ± 2.37 2279341.30 ± 148791.55 1934573.60 ± 209237.06 4213914.90 ± 321395.67 279-294 2 21.00 ± 1.41 2502538.50 ± 2946.51 1923736.50 ± 6299.61 4426275.00 ± 3353.10 295-310 3 25.67 ± 2.08 2664289.33 ± 160283.40 2338934.00 ± 236175.00 5003223.33 ± 396043.33 311-326 2 29.50 ± 0.71 2877886.00 ± 9439.88 2545201.50 ± 68008.82 5423087.50 ± 77448.70 327-345 2 29.50 ± 0.71 2889529.50 ± 56945.43 2571177.50 ± 9515.54 5460707.00 ± 47429.89

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Table. 4.5.5.2.Regression equation for relationship of fecundity with total length (TL), body weight (B.Wt), gonad weight (G.Wt) and gonadal length right (G.L.R) and left (G.L.L) of Acanthopagrus arabicus .

Regression Standard error t-test Relationships No of fish r² P a b a b a b Fecundity & TL -8.648 6.240 1.259 0.523 0.748 -6.867 11.932 0.000 Fecundity & B.Wt 0.277 2.406 0.559 0.220 0.713 0.495 10.917 0.000 Fecundity & G.Wt 50 4.409 1.659 0.203 0.169 0.667 21.748 9.809 0.000 Fecundity & G.L.R -3.675 5.280 0.591 0.310 0.858 -6.221 17.023 0.000 Fecundity & G.L.L -2.992 4.959 0.719 0.380 0.780 -4.163 13.043 0.000

98

7.5

y = 6.2404x - 8.6482 r² = 0.7479 7

6.5

Fecundity 6

5.5

5 2.3 2.35 2.4 2.45 2.5 2.55 Total length of fish (mm)

Fig. 4.5.5.1. Relationship between fecundity and total length of Acanthopagrus arabicus .

99

7.5 y = 2.4057x + 0.277 r² = 0.7129

7

6.5

Fecundity 6

5.5

5 2 2.1 2.2 2.3 2.4 2.5 2.6 2.7 2.8 2.9 3 Body weight of fish (g)

Fig. 4.5.5.2. Relationship between fecundity and body weight of Acanthopagrus arabicus .

100

7 y = 1.6593x + 4.4087 6.8 r² = 0.6672

6.6

6.4

6.2

6

Fecundity 5.8

5.6

5.4

5.2

5 0.8 0.9 1 1.1 1.2 1.3 1.4 1.5 1.6 Ovary weight (g)

Fig. 4.5.5.3. Relationship between fecundity and ovary weight of Acanthopagrus arabicus .

101

7.5

y = 4.9588x - 2.9924 r² = 0.7799 7

6.5

Fecundity 6

5.5

5 1.75 1.8 1.85 1.9 1.95 2 2.05 Right Ovary length (mm)

Fig. 4.5.5.4. Relationship between fecundity and ovary length (right lobe) of Acanthopagrus arabicus .

102

7 y = 5.2797x - 3.6754 6.8 r² = 0.8579

6.6

6.4

6.2

6

Fecundity 5.8

5.6

5.4

5.2

5 1.75 1.8 1.85 1.9 1.95 2 2.05 Left Gonad length (mm)

Fig. 4.5.5.5. Relationship between fecundity and ovary length (left lobe) of Acanthopagrus arabicus .

103

600000

500000

400000

300000 Number Number Ova of 200000

100000

0 Anterior Middle Posterior Ovary (right lobe)

Fig. 4.5.5.6. Number of ova in anterior, middle and posterior parts of the ovary (right lobe) of Acanthopagrus arabicus .

104

500000

450000

400000

350000

300000

250000

200000 Number Number Ova of

150000

100000

50000

0 Anterior Middle Posterior Ovary (left lobe)

Fig. 4.5.5.7. Number of ova in anterior, middle and posterior parts of the ovary (left lobe) of Acanthopagrus arabicus .

105

4.6. Diet of Acanthopagrus arabicus

4.6.1. General composition

A total of 1400 stomachs examined of which stomachs with food items categorized into four groups, i.e. Teleost (different types of small fishes and Juveniles), Arthropods (shrimps, prawns and crabs) Molluscs (bivalves, gastropods and cephalopods) and Miscellaneous (unidentifiable food items, semi digested food and animal derivatives like: eggs, shells, scales, bones, eyes, fins, chela and other appendages etc.). Similar food items existed in both male and female stomachs. In the same way, stomachs classified according to its fullness and points given accordingly. Gorged stomach got 100 points in percent. (Plate 4)

106

Plate. 4. Dissected Acanthopagrus arabicus showing gut within body cavity and extracted gorged stomach with its contents.

107

4.6.2. Feeding intensity on the basis of different seasons and size

Fish with gorged and full stomachs considered as active feeders, ¾ full and ½ full as moderate feeders and ¼ full and barely full as poor feeders in present study. Active feeders amongst male and female Acanthopagrus arabicus showed slightly different trends in different seasons. In female active feeding was observed during spring (2011), autumn, winter and spring (2012) and winter and spring (2013). Nonetheless, highest percentage of moderate feeders observed during summer (2011, 2012 and 2013) and spring (2013). While highest percentage of poor feeders recorded in autumn (2011, 2012 and 2013) (Table 4.6.2.1).

Table. 4.6.2.1. Percent occurrence of food items in the stomach of female Acanthopagrus arabicus during different seasons of the study period.

No. Gorged Full 3/4 Full 1/2 Full 1/4 Full Barely Full Empty Season of Fish 100% 75% 50% 25% 12% 6% 0

autumn 40 5.00 7.50 10.00 10.00 10.00 27.50 30.00

winter 62 6.45 8.06 16.13 12.90 11.29 25.81 19.35

2011 spring 56 7.14 17.86 10.71 10.71 10.71 17.86 25.00

summer 72 1.39 5.56 11.11 20.83 11.11 22.22 27.78

Total 230 1.67 3.25 4.00 4.54 3.59 7.78 8.51

autumn 31 12.90 16.13 6.45 9.68 6.45 22.58 25.81

winter 61 13.11 11.48 16.39 9.84 8.20 14.75 26.23

2012 spring 57 14.04 12.28 15.79 10.53 8.77 12.28 26.32

summer 62 4.84 4.84 12.90 22.58 12.90 12.90 29.03

Total 211 3.74 3.73 4.29 4.39 3.03 5.21 8.95

autumn 46 4.35 8.70 10.87 13.04 19.57 23.91 19.57

winter 73 10.96 12.33 6.85 17.81 13.70 24.66 13.70

2013 spring 73 5.48 16.44 15.07 12.33 15.07 16.44 19.18

summer 68 4.41 5.88 5.88 17.65 17.65 19.12 29.41

Total 260 2.10 3.61 3.22 5.07 5.50 7.01 6.82

108

While in male Acanthopagrus arabicus , active feeding intensity observed during winter (2011), autumn and winter (2012) and autumn (2013). Moderate feeders were dominant in spring (2011), summer (2012), autumn and summer (2013). Although highest percentage of poor feeding intensity was recorded in autumn (2011) and spring (2012 and 2013). Empty stomachs found in all the seasons with highest percentage during summers (2011, 2012 and 2013) regardless of gender (Table 4.6.2.2).

Table. 4.6.2.2. Percent occurrence of food items in the stomach of male Acanthopagrus arabicus during different seasons of the study period.

No. Gorged Full 3/4 Full 1/2 Full 1/4 Full Barely Full Empty Season of Fish 100% 75% 50% 25% 12% 6% 0

autumn 45 6.67 6.67 15.56 13.33 4.44 26.67 26.67

winter 71 8.45 8.45 21.13 12.68 8.45 16.90 23.94

2011 spring 59 5.08 8.47 16.95 16.95 13.56 13.56 25.42

summer 81 2.47 4.94 8.64 19.75 16.05 13.58 34.57

Total 256 1.89 2.38 5.19 5.23 3.54 5.89 9.22

autumn 29 6.90 17.24 13.79 13.79 6.90 17.24 24.14

winter 56 8.93 12.50 12.50 16.07 8.93 14.29 26.79

2012 spring 46 10.87 8.70 6.52 13.04 15.22 17.39 28.26

summer 55 3.64 7.27 10.91 21.82 9.09 14.55 32.73

Total 186 2.53 3.81 3.64 5.39 3.34 5.29 9.33

autumn 41 4.88 12.20 17.07 14.63 12.20 17.07 21.95

winter 69 8.70 7.25 15.94 8.70 13.04 18.84 27.54

2013 spring 61 6.56 8.20 13.11 9.84 14.75 19.67 27.87

summer 86 2.33 4.65 9.30 20.93 13.95 17.44 31.40

Total 257 1.87 2.69 4.62 4.51 4.50 6.09 9.06

109

Observations on feeding intensity in different size groups of male Acanthopagrus arabicus showed active feeding in larger specimens of size groups 301-317 mm and 318-334 mm while moderate feeders were observed in variety of size groups including 216-232 mm, 284-300 mm, 301-317 mm and 318-334 mm. Highest percentages of poor feeder and empty stomach were recorded in size group 165-181 mm and 199-215 mm respectively (Table 4.6.2.3).

Table. 4.6.2.3. Percent occurrence of food items in the stomach of male Acanthopagrus arabicus in different size groups.

No. 3/4 1/4 Gorged Full 1/2 Full Barely Size group of Full Full Empty 0 100% 75% 25% Full 6% Fish 50% 12% 165-181 36 - 2.78 11.11 5.56 22.22 27.78 30.56 182-198 125 0.8 4.00 4.00 17.60 15.20 24.80 33.60 199-215 117 7.69 5.98 11.97 8.55 10.26 21.37 34.19 216-232 147 0.68 6.12 17.69 21.09 9.52 10.88 34.01 233-249 119 11.76 10.92 5.88 18.49 14.29 10.92 27.73 250-266 67 8.96 10.45 17.91 13.43 7.46 25.37 16.42 267-283 31 16.13 6.45 19.35 16.13 25.81 9.68 6.45 284-300 15 20.00 13.33 33.33 20.00 - - 13.33 301-317 17 5.88 29.41 47.06 11.76 - 5.88 - 318-334 10 10.00 30.00 10.00 20.00 - 10.00 20.00 335-354 15 6.67 20.00 33.33 - - 13.33 26.67 Total 699 8.05 12.68 19.24 13.87 9.52 14.55 22.09

110

In female, active feeders represented in size groups 301-317 mm and 318-334 mm. While moderate feeders were dominant amongst the size groups 216-232 mm, 301-317 mm and 335-354 mm. Size group 165-181 mm recorded with highest percentage of poor feeding intensity similar to male but difference observed in percent empty stomachs which occurred in size group of 284-300 mm in female (Table 4.6.2.4).

Table. 4.6.2.4. Percent occurrence of food items in the stomach of female Acanthopagrus arabicus in different size groups.

Size group No of Gorged Full 3/4 1/2 1/4 Barely Empty 0 Fish 100% 75% Full Full Full Full 6% 50% 25% 12% 165-181 21 - 4.76 - 4.76 23.81 47.62 19.05 182-198 47 2.13 12.77 8.51 17.02 14.89 17.02 27.66 199-215 133 - 0.75 10.53 12.03 21.05 26.32 29.32 216-232 145 2.76 11.03 14.48 24.83 9.66 13.79 23.45 233-249 138 15.94 7.97 9.42 11.59 9.42 19.57 26.09 250-266 103 4.85 18.45 13.59 6.80 12.62 20.39 23.30 267-283 40 20.00 7.50 10.00 15.00 12.50 15.00 20.00 284-300 26 3.85 23.08 7.69 7.69 3.85 23.08 30.77 301-317 13 15.38 30.77 30.77 7.69 7.69 7.69 - 318-334 18 44.44 22.22 - 22.22 - 11.11 - 335-354 17 - 11.76 35.29 29.41 - 11.76 11.76 Total 701 9.94 13.73 12.75 14.46 10.50 19.40 19.22

111

4.6.3. Seasonal variation in the percentage composition of food

Teleost group observed to be the dominant group in the stomachs of male and female Acanthopagrus arabicus in most of the seasons. Highest percentage of Teleost was recorded during winter (2011, 2012 and 2013) in female (Figure 4.6.3.1) and with a variation, winter (2011) and autumn (2012 and 2013) in male (Figure 4.6.3.2). Whereas Arthropods dominated the spring (2011, 2012 and 2013) in female and winter and spring (2011, 2012 and 2013) in male. Mollusks showed comparatively high percentage in females than in males and low percentage of miscellaneous group recorded during almost all the seasons in both male and female stomachs.

112

14.00

12.00

10.00

8.00

6.00 Percent total points Percent 4.00

2.00

0.00 spring spring spring winter winter winter autumn autumn autumn summer summer summer 2011 2012 2013

Teleost Mollusc Arthropods Misc

Fig. 4.6.3.1. Percent total points of food items in female Acanthopagrus arabicus during different seasons.

113

16.00

14.00

12.00

10.00

8.00

6.00 Percent total points Percent 4.00

2.00

0.00 spring spring spring winter winter winter autumn autumn autumn summer summer summer 2011 2012 2013

Teleost Mollusc Arthropods Misc

Fig. 4.6.3.2. Percent total points of food items in male Acanthopagrus arabicus during different seasons.

114

4.6.4. Percentage composition of food in relation to size of the fish

In female Acanthopagrus arabicus highest percentages of all identifiable food item groups (Teleost, Arthropods and Mollusks) recorded in size group 318-334 mm (Figure 4.6.4.1), on contrary male showed highest percentage of Teleost and Mollusks in size group 284- 300 mm and Arthropods in size group 301-317 mm (Figure 4.6.4.2).

Generally, miscellaneous group found to be in low percentage in all size groups of male and female Acanthopagrus arabicus . However, Size group 301-317 mm recorded with slightly greater percentage of miscellaneous group in both male and female.

115

35.00

30.00

25.00

20.00

15.00 Percent totalPercentpoints 10.00

5.00

0.00 165-181 182-198 199-215 216-232233-249250-266267-283 284-300 301-317 318-334 335-354

Teleost Mollusc Arthropod Misc

Fig. 4.6.4.1. Variation in percent total points of food items amongst different size groups of female Acanthopagrus arabicus .

116

35.00

30.00

25.00

20.00

15.00 Percent totalPercentpoints

10.00

5.00

0.00 165-181 182-198 199-215 216-232 233-249 250-266 267-283 284-300 301-317 318-334 335-354

Teleost Mollusc Arthropod Misc

Fig. 4.6.4.2. Variation in percent total points of food items amongst different size groups of male Acanthopagrus arabicus .

117

4.6.5. Gastro-somatic Index (GaSI) and Relative gut length (RLG)

Monthly variation in Gastro-somatic index calculated in male and female Acanthopagrus arabicus to observe feeding intensity in both sexes. Pattern of increase and decrease in Gastro-somatic was slightly different in both sexes. In male, Box plot showed uniformly distributed (symmetrical) data found in August (Figure 4.6.5.2) while variation amongst both sexes can be seen by positively and negatively skewed data recorded in different months (Figure 4.6.5.1 and 4.6.5.2).

118

Fig. 4.6.5.1. Gastro-somatic index (GaSI) of female Acanthopagrus arabicus .

119

Fig. 4.6.5.2. Gastro-somatic index (GaSI) of male Acanthopagrus arabicus .

120

Mean value and standard deviation of Relative gut length (RLG) presented in Table 4.6.5.1 which showed variation from 1.08 to 1.40 in female and 0.94 to 1.33 in male. Smaller values of RLG in both male and female suggested that Acanthopagrus arabicus is a carnivore fish.

Table. 4.6.5.1. Mean and standard deviation for Relative gut length (RLG) of female and male Acanthopagrus arabicus in different size groups.

RLG Length group (mm) Female Male

165-181 1.36 ± 0.12 1.33 ± 0.13

182-198 1.29 ± 0.10 1.24 ± 0.11

199-215 1.19 ± 0.10 1.21 ± 0.10

216-232 1.17 ± 0.12 1.21 ± 0.92

233-249 1.14 ± 0.13 1.05 ± 0.11

250-266 1.19 ± 0.14 1.08 ± 0.14

267-283 1.28 ± 0.09 1.09 ± 0.11

284-300 1.29 ± 0.25 0.98 ± 0.06

301-317 1.40 ± 0.37 1.16 ± 0.24

318-334 1.10 ± 0.33 0.98 ± 0.14

335-354 1.08 ± 0.02 0.94 ± 0.10

121

4.6.6. Index of preponderance

Estimated Index of preponderance suggested that Teleost and Arthropod groups closely related amongst male and female Acanthopagrus arabicus (Plate 5). By the help of Index of preponderance grade allotted to groups on the basis of preference of food items by the fish. Group with highest preponderance got grade I, comparatively less got grade II, lesser grade III and least preferred as grade IV.

Plate 5. Preponderance of food items in female and male Acanthopagrus arabicus along with the food items recovered from gut.

122

Highly preferred food item recorded in female was Teleost group with grade I and comparatively less preferred group Arthropod with grade II (Table 4.6.6.1). On contrary, Arthropod was highly preferred group (Grade I) and comparatively less preferred Teleost got grade II in male (Table 4.6.6.2). However, in both male and female Acanthopagrus arabicus group Mollusk and Miscellaneous showed similarity in grades i.e. III and IV respectively.

Table. 4.6.6.1. Index of preponderance of food items on female Acanthopagrus arabicus .

% composition of item Food index of Gradin by VO Items preponderance g Volume Occurrence 300.2 Teleost 33.40 8.99 38.54 I 7 162.3 Femal Mollusk 24.03 6.76 20.84 III 3 e 290.6 Arthropod 32.70 8.89 37.31 II 6 Misc. 9.72 2.66 25.84 3.32 IV 779.1

0

Table. 4.6.6.2. Index of preponderance of food items on male Acanthopagrus arabicus .

% composition of item by Food Items VO index of preponderance grading Volume Occurrence

Teleost 34.35 8.91 306.13 38.98 II

Mollusk 22.53 5.91 133.12 16.95 III Male

Arthropod 36 9.30 334.85 42.64 I

Misc. 6.76 1.65 11.16 1.42 IV

785.26

123

4.7. Estimation of macro-nutrients

The concentrations of macronutrients in twenty four samples (12 samples each of meat and gills) along with average body weight and average total length in different months are presented in Table 4.7.1. The concentrations of calcium, potassium and sodium demonstrated statistically significant difference (p < 0.001) between the meat and the gills of the fish. The concentrations of calcium in gills were significantly higher compared to those in meat. On the contrary, the concentrations of potassium and sodium in gills were significantly lower than those in meat. Nonetheless, the concentrations of magnesium revealed statistically non-significant difference between the gills and the meat.

The meat of the fish revealed statistically non-significant difference of all the macronutrients among various months. Nevertheless, the meat exhibited statistically significant difference (p < 0.001) among the concentrations of four different macronutrients. In meat, sodium recorded highest average concentration (5.41 + 0.68 %) while magnesium showed lowest average concentration (0.24 + 0.07 %) (Table 4.7.2a). However, the gills of the fish demonstrated statistically significant difference (p < 0.01) of all the macronutrients among various months. The highest concentrations of calcium (85.31 %), magnesium (0.43 %), potassium (1.88 %) and sodium (4.68 %) in gills were found in October, July, September and December respectively (Table 4.7.1). Moreover, the gills disclosed statistically significant difference (p < 0.001) among the concentrations of four different macronutrients. In gills, calcium recorded highest average concentration (57.72 + 14.24 %) while magnesium showed lowest average concentration (0.31 + 0.05 %) (Table 4.7.2b). In fish, the concentrations of macronutrients also depend upon its body weight and length. The present study demonstrated statistically significant (p < 0.05) correlation of body weight with calcium and magnesium while it revealed non-significant correlation of the body weight with potassium and sodium.

124

Statistically significant correlations (p < 0.05) were found between the body weight and the concentrations of calcium and magnesium of the meat while non-significant correlations were determined between the body weight and the concentrations of potassium and sodium of the meat (Table 4.7.3a). Nonetheless, sodium concentrations in the gills differed significantly (p < 0.05) with the body weight (Table 4.7.3b). Moreover, the concentration of sodium of the gills differed significantly (p < 0.05) with the body weight. However, non-significant correlations were noted between the body weight and the concentrations of magnesium and potassium, which was found in the gills.

125

Table 4.7.1. Concentrations of nutrients (%), average body weight (gm) and average total length (mm) of Acanthopagrus arabicus during different months.

Total Body Calcium % Magnesium% Potassium% Sodium% Month length weight

Meat Gills Meat Gills Meat Gills Meat Gills (mm) (g) Jan 1.37 37.83 0.22 0.24 3.97 1.11 4.76 3.1 232.33 265.33 Feb 1.46 57.79 0.19 0.29 3.47 0.83 5.79 3.11 233.33 240.67 Mar 1.16 42.51 0.16 0.27 1.79 0.9 5.72 3.24 231 246.67 Apr 4.31 40.93 0.32 0.28 3.43 1 4.71 3 231 251.67 May 3.99 66.32 0.43 0.33 3.09 1.41 7.12 3.76 243 290 Jun 2.31 62.26 0.21 0.31 3.3 0.72 5.19 3.11 219 257 Jul 1.64 63.63 0.21 0.43 3.57 1.19 5.96 3.81 220.67 241 Aug 1.86 44.8 0.19 0.27 3.76 1.26 5.17 3.58 207.33 186.67 Sep 1.15 71.5 0.21 0.33 4.01 1.88 5.18 2.35 234 253.67 Oct 2.1 85.31 0.25 0.35 3.57 1.43 4.91 3.67 244.67 288.33 Nov 1.6 54.22 0.25 0.28 3.69 1.09 4.93 3.7 249.67 300 Dec 2.94 65.53 0.28 0.36 3.67 1.49 5.5 4.68 267 345

126

Table 4.7.2a. Descriptive statistics, estimated daily intake (EDI) and daily dietary reference intake (DRI in mg) (NIH, USA, 2017) for meat of Acanthopagrus arabicus .

Elements Skewness Kurtosis Mean ± SD DRI EDI (%) SE SE

Calcium 2.16 ± 1.06 1.222 0.637 0.413 1.232 1000 0.040

Magnesium 0.24 ± 0.07 1.680 0.637 3.273 1.232 (413-317) 0.004

Potassium 3.44 ± 0.58 -2.314 0.637 6.539 1.232 4700 0.063

Sodium 5.41 ± 0.68 1.531 0.637 2.897 1.232 1500 0.103 *SD= standard deviation, SE= standard error

Table 4.7.2b. Descriptive statistics, estimated daily intake (EDI) and daily dietary reference intake (DRI in mg) (NIH, USA, 2017) for gills of Acanthopagrus arabicus .

Skewness Kurtosis Elements Mean ± SD DRI EDI (%) SE SE

Calcium 57.72 ± 14.24 0.254 0.637 -0.413 1.232 1000 1.030 Magnesium 0.31 ± 0.05 0.980 0.637 1.170 1.232 (413-317) 0.005 1.19 ± 0.33 Potassium 0.597 0.637 0.366 1.232 4700 0.022 3.43 ± 0.58 Sodium 0.384 0.637 1.521 1.232 1500 0.065 *SD= standard deviation, SE= standard error

127

Table 4.7.3a: Pearson’s correlation between body weight of Acanthopagrus arabicus and the concentration of various macronutrients in meat. Body Calcium Potassium Magnesium Sodium weight (g) Calcium Correlation 1 Sig. (2-tailed) Potassium Correlation -0.027 1

Sig. (2-tailed) 0.935 Magnesium Correlation 0.858** 0.070 1 Sig. (2-tailed) 0.000 0.829 Sodium Correlation 0.243 -0.394 0.443* 1 Sig. (2-tailed) 0.447 0.205 0.149 Body weight Correlation 0.306* 0.071 0.490* 0.088 1 (g) Sig. (2-tailed) 0.333 0.826 0.105 0.785 **. Correlation is significant at the 0.01 level (2-tailed). *. Correlation is significant at the 0.05 level (2-tailed).

128

Table 4.7.3b: Pearson’s correlation between body weight of Acanthopagrus arabicus and concentrations of macronutrients in gills. Body Calcium Magnesium Potassium Sodium weight (g)

Calcium Correlation 1

Sig. (2-tailed)

Magnesium Correlation 0.628* 1

Sig. (2-tailed) 0.029

Potassium Correlation 0.324* 0.393* 1

Sig. (2-tailed) 0.304 0.205

Sodium Correlation 0.096 0.421* 0.083 1

Sig. (2-tailed) 0.767 0.173 0.797 Body weight Correlation 0.631* 0.271 0.277 0.540* 1 (g) Sig. (2-tailed) 0.028 0.395 0.384 0.070 *. Correlation is significant at the 0.05 level (2-tailed).

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4.8. Estimation of trace elements

Present result showed monthly fluctuations in estimated trace elements in Acanthopagrus arabicus . Highest concentration of Iron (Fe) in gills (Figure 4.8.1) observed in November while in meat (Figure 4.8.2) highest concentration recorded in August. However lowest concentration observed in February and March respectively.

Similar trends observed in rest of the trace elements i.e. in gills, Chromium (Cr) ↑ November and ↓ June (Figure 4.8.3), Manganese (Mn) ↑ July & December and ↓ March (Figure 4.8.5) and Zinc (Zn) ↑ May and ↓ April (Figure 4.8.7). Whereas in meat Chromium (Cr) ↑ November and ↓ May (Figure 4.8.4), Manganese (Mn) ↑ November and ↓ March (Figure 4.8.6) and Zinc (Zn) ↑ June and ↓ December (Figure 4.8.8).

Toxic elements such as Lead and Cadmium were not found in Acanthopagrus arabicus as samples run for detection. While Mercury (Hg) observed in very low concentration in both gills (Figure 4.8.9) and meat of the fish (Figure 4.8.10).

130

Fe (ppm) in Gills 200.00

180.00

160.00

140.00

120.00

100.00

80.00

60.00

40.00

20.00

0.00 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Fig.4.8.1. Concentration of Iron in gills of Acanthopagrus arabicus in different months.

131

Fe (ppm) in Meat 80.00

70.00

60.00

50.00

40.00

30.00

20.00

10.00

0.00 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Fig. 4.8.2. Concentration of Iron in meat of Acanthopagrus arabicus in different months.

132

Cr (ppm) in Gills 7

6

5

4

3

2

1

0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Fig. 4.8.3. Concentration of Chromium in gills of Acanthopagrus arabicus in different months.

133

Cr (ppm) in Meat 9

8

7

6

5

4

3

2

1

0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Fig. 4.8.4. Concentration of Chromium in meat of Acanthopagrus arabicus in different months.

134

Mn (ppm) in Gills 20.00

18.00

16.00

14.00

12.00

10.00

8.00

6.00

4.00

2.00

0.00 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Fig. 4.8.5. Concentration of Manganese in gills of Acanthopagrus arabicus in different months.

135

Mn (ppm) in Meat 6.00

5.00

4.00

3.00

2.00

1.00

0.00 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Fig. 4.8.6. Concentration of Manganese in meat of Acanthopagrus arabicus in different months.

136

Zn (ppm) in Gills 160.00

140.00

120.00

100.00

80.00

60.00

40.00

20.00

0.00 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Fig. 4.8.7. Concentration of Zinc in gills of Acanthopagrus arabicus in different months.

137

Zn (ppm) in Meat 14.00

12.00

10.00

8.00

6.00

4.00

2.00

0.00 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Fig. 4.8.8. Concentration of Zinc in meat of Acanthopagrus arabicus in different months.

138

Hg (ppb) in Gills 0.16

0.14

0.12

0.10

0.08

0.06

0.04

0.02

0.00 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Fig. 4.8.9. Concentration of Mercury in gills of Acanthopagrus arabicus in different months.

139

Hg (ppb) in Meat 0.25

0.20

0.15

0.10

0.05

0.00 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Fig. 4.8.10. Concentration of Mercury in meat of Acanthopagrus arabicus in different months.

140

5. Discussion

Fishery in any country is the constituent of its national economy (Kesteven, 1996) as it provides revenue to the country. Nonetheless sustainable fisheries management is required for long term benefits along with the information on stock’s life history processes (Al-Kiyumi, 2013).

As for fishing, several gears used and in Arabian Sea resources have been affected by trawl fishing activities for the last several years (Mathews, et al., 2001). Therefore, regulations are needed for sustainable fishery resource management especially in Pakistan and by reducing over-exploitation, fisheries could play a vital role in national GDP. Husain (2014) suggested ban on over-exploitation as a part of fishery laws.

In present work several aspects along with life history processes (e.g. length- weight relationship, length frequency distribution, reproduction pattern, spawning, feeding habits etc.) are discussed which could help in fisheries management practices for commercially important fish Acanthopagrus arabicus in particular such as landing data, gear used for catch and export trends. The review of the catches could be possible tool for estimation of effects of marine protected areas on local fisheries (Batista et al., 2015).

Hussain et al., (2010) presented Length-weight relationship for two species of the same family from Karachi coast. Results indicated isometric growth for Acanthopagrus latus (b = 3.015) and Acanthopagrus berda (b = 3.092). On contrary Hameed et al. (2013) observed negative allometric growth pattern in Acanthopagrus berda from Karachi coast. While in present study value of ‘b’ deviated from 3 consequently, positive allometry, negative allometry and isometry observed in Acanthopagrus arabicus during different seasons of the study period as Patra et al., (2000) suggested that variation in the obtained ‘b’ value other than 3 could be because of seasonal changes.

Similarly, seasonal variation in value of ‘b’ and negative allometric growth from this region observed by different authors including, Ahmed et al., (2013), Ahmed et al., (2014), Ahmed et al., (2015), Elahi et al., (2016), Khawar et al., (2015), Mahmood et al., (2012), Khatoon et al., (2014) and Safi et al., (2014).

Various size ranges observed in Acanthopagrus arabicus during this study which was in accordance to the findings of Adebiyi (2013) for a different species. Present data provided length frequency distribution for the period of three years which could be of help

141 for size structure studies of population of the fish in environment (Bagenal, 1978) by the fisheries management agencies (Mendes et al., 2004).

As in present study, increase in length frequency corresponded to fish growth in certain size ranges was observed (Andem et al., 2013) nonetheless direct proportion between length frequency distribution and increase in length of the fish could not be suggested (Olagbemide, 2010).

Presented size ranges for length frequency distribution of Acanthopagrus arabicus can vary with other studies as length frequency distribution influenced by regions of sample collected, ecological conditions (Mathialagan et al., 2013), water temperature and food availability (Weatherley and Gill, 1987).

Present study suggested no sexual dimorphism amongst male and female Acanthopagrus arabicus from Karachi coast, which is in accordance with the observations provided by Mahmoud et al., (2016) which showed no sexual dimorphism in the specie belonged to same genus i.e. Acanthopagrus bifasciatus from Egypt.

Linear regression applied in present study to observe correlation between different morphometric characters and total length/size of the fish. Similar method used by Khumar and Siddiqui (1991), Rizkalla (1994), Jaiswer et al., (2004) and Safi et al., (2014) and provided data on relationship between length and morphometric characters in different species.

While, from this region numerous workers have also provided morphometric data including Nasir et al. (2017), Safi et al. (2014), Naeem et al. (2011), Naeem and Salam (2005) and Salam and Naeem (2004) etc.

Macroscopic and microscopic observation in present study during spawning and non-spawning periods suggested Acanthopagrus arabicus as protandrous hermaphrodite, as other species belonged to genus Acanthopagrus such as Acanthopagrus latus (Abou- Seedo et al., 2003 and Hesp et al., 2004) and Acanthopagrus berda (Shilta et al., 2018).

Gonadal development trends observed in Acanthopagrus arabicus were not significantly different as described in other sparid Acanthopagrus latus by Abu-Hakima (1984), Abou-Seedo et al., (2003), Hesp et al., (2004) and ovarian development in other teleost species provided by earlier workers such as Abou-Seedo and Al-Khatib (1995), Coward and Bromage (1998), Maddock and Burton (1999) etc.

142

Present study observed developing stages in both testicular and ovarian parts of the ovotestes and considered ovotestes with testicular dominant tissues as male and ovotestes with ovarian dominant tissues as female. Transitional stages observed and found fish of size above 355 mm were female. Histological study observed females with active maturing ovary contained lipid vesicles and yolk granules in perinucleolar stages, which is quite similar to observation by Abou-Seedo et al., (2003) in Acanthopagrus latus .

In present study, spawning season of Acanthopagrus arabicus determined by the help of macroscopic and histological study of mature gonads and mean values of monthly GSI, a common approach used for evaluation of reproductive or spawning season (Fowler et al., 2000). Gonadosomatic index along with other techniques such as histological study and oocyte diameter become more effective indicator for spawning period (McDonough et al., 2003).

This study suggested GSI values increased in the winter, similar finding provided in Acanthopagrus latus from Japan (Abol-Munafi and Umeda, 1994). Acanthopagrus arabicus spawn for a period of four months, suggested in present study could be relate to the similar findings in Acanthopagrus latus by Abou-Seedo et al., (2003) from Kuwait, Hesp et al., (2004) from Australia and Vahabnezhad et al., (2016) from Iran.

Mean GSI values observed in both male and female Acanthopagrus arabicus showed identical trend which is similar to observation of Hesp et al., (2004) for Acanthopagrus latus .

Fehri-Bedoui and Gharbi (2008) observed no significant difference from 1:1 standard sex ratio in Pomadasys incisus which is similar to present finding, as sex ratio of Acanthopagrus arabicus showed standard ratio of 1:1 (Yankson and Azumah, 1993). Chi- square used in present study to test the significance of the sex ratio.

However, in present study there were insignificant differences observed in sex ratio during different months of the study period and in different size groups of the fish as well. Habitat preferences by mature individuals (Reynolds, 1974) and migration (Collignon, 1960) could be possible reasons for deviation of sex ratio.

In this study, sex ratio in different sizes of Acanthopagrus arabicus showed higher male ratio in smaller sizes higher female ratios in large sizes as exhibited by the protandrous hermaphrodite species. Similar findings presented by Abou-Seedo et al.,

143

(2003) in another sparid Acanthopagrus latus . As suggested by Allsop and West (2004) biased sex ratio more common in protogynous hermaphrodite species than in protandrous hermaphrodite species, present study is in accordance with this study.

Present work suggested larger ovary carried highest number of eggs in Acanthopagrus arabicus and variation in fecundity of same size ovaries observed in the study. Variation in fecundity also observed by Pillay and Rao (1961), Doha and Hye (1970) and Kjesbu et al., (1996).

Kingdom and Allison (2011) observed best correlation (0.57) amongst fecundity and body weight of the fish. However, present study showed best correlation amongst fecundity and gonad length (0.85). These differences showed different relationships in variety of fishes. Such as Nandikeswari and Anandan (2013) found highly significant correlation between fecundity and Gonad weight. Similar approach used by Bahuguna and Khatri (2009) on Loach provided relationship between fecundity and ovary weight, ovary length, total length and body weight of the fish. They found significant relationship amongst these.

Present study suggested increase in fecundity with increase in size and body weight of the fish similar result observed by Sarker et al., (2002) in Mystus gulio . Particularly studies on fecundity of different sparids provided by Norriss et al., (2002) on Acanthopagrus butcheri , Hesp et al., (2004) worked on Rhabdosargus sarba while, Sarre and Potter (1999) presented observations on Acanthopagrus butcheri and Abol-Munafi and Umeda (1994) and Fairclough et al., (2004) selected Acanthopagrus latus for similar studies. Roubal (1994) observed fecundity in another sparid Acanthopagrus australis .

Studies on diet composition of sparids including Acanthopagrus arabicus are very limited, especially from Arabian Sea. There are several factors that influenced diet composition of the fish such as, temperature of water, feeding habitat and season etc. (Nikolskii, 1963 and Zarbalieva, 1973).

Most of the studies on detailed diet of Acanthopagrus spp . suggested that main food items included fish, cephalopods, bivalves, gastropods and decapods etc. (Vahabnezhad et al., 2016). Which is quite similar to current findings in Acanthopagrus arabicus i.e. main three groups found in the gut were teleost, mollusk and arthropod along with the miscellaneous group that included animal derivatives like, eggs, shells, scales,

144 bones, chela, fins and unidentifiable items etc. Hence, present observations could suggest Acanthopagrus arabicus as an opportunistic feeder (Platell et al., 2007).

Seasonal changes in the diet of the Acanthopagrus arabicus observed. All the food items groups showed variation in each season. Variations observed during present study could be influence by factors like availability of the food items recovered from the gut in different seasons. Similar study by Sourinejad et al., (2015) observed seasonal variation amongst Gastrosomatic Index in Acanthopagrus latus . In present study, difference observed between Gastrosomatic Index in different seasons as well as in male and female Acanthopagrus arabicus of same season.

Food items recovered from the gut of Acanthopagrus arabicus in this study showed overall highest concentration of teleost and arthropods (Sourinejad et al., 2015 and Vahabnezhad et al., 2016). Gut content analysis like stomach fullness and occurrence of the food items in percentages used by Khan and Hoda (1993) and Khan et al., (2014) used in present study.

The results demonstrate that the meat and the gills of Acanthopagrus arabicus is an important source of calcium, potassium, magnesium and sodium, which could be consumed by humans to recover from their deficiencies. The gills of the fish exhibited the highest concentrations of calcium, which may be an important dietary source to address human diseases such as osteoporosis and proper functioning of heart, nerves and muscles (Peacock, 2010 and Pravina et al., 2013). Magnesium is required for a variety of physiological functions of humans (Vormann, 2003). It helps to produce hormones, maintains heartbeat and muscles movement and regulates other essential nutrients like calcium, potassium and sodium in the human body (Winiarska-Mieczan, 2014). Potassium and sodium ions are indispensable for the maintenance of cellular homeostasis of human tissues. These electrolytes help to maintain osmotic pressure, distribute water in different body fluid areas, maintain pH, regulate cardiovascular and other muscular functions and act as cofactor for enzymes (Pohl, et al, 2013). The current study suggests that the body weight of fish could be used to estimate the concentration of various macronutrients in the meat and gills of fish. The study could be extended to reveal the association between body weight and different nutrients, which are found in various body parts of other fish species. The dietary reference intake (DRI)

145 per day, which was recommended by National Institutes of Health, U.S.A (NIH, 2017), is provided to compare them with the estimated daily intake (EDI) values of macronutrients calculated in meat and gills so as to recommend the meat and the gills of Acanthopagrus arabicus for its required dietary intake to maintain good health of the people, particularly of nutrient deficient population of the world. Acanthopagrus arabicus is a good source of calcium, magnesium, potassium and sodium. The meat and the gills of the fish could be consumed by the population, who lack these nutrients in their diet since the nutrients are essentially required for proper functioning of different organs and organ systems of humans.

Present observations showed difference in trace elements/metals concentrations amongst gills and meat in different months of the study, similar observations done by Abdel-Baki et al., (2011) presented on gills and meat of tilapia fish from Saudi Arabia and these differences could be because of behaviour of the fish or feeding habit such as study by Usero et al., (2003) suggested eels with higher concentration of metals than in common sole while both belonged to different areas of predation. Canli and Atli (2003) studied variation in metal accumulation amongst different body parts of the fish. Naga and Allam (1999) studied concentrations of different trace metal in tissues of Tillapia zilli from Eygpt. Trace elements estimated in this study were also determine by Tariq et al., (1998) in seven different fish species from same coast.

Lead and Cadmium both metals are known for causing deformities in fish (Kingsford and Gray, 1996) were not found in the samples of Acanthopagrus arabicus during present study. However a small amount of mercury was observed in gills and meat of the fish. Chen (2002) observed higher concentration of mercury in Acanthopagrus berda and suggested that levels of metal concentration could be used as bio-indicator for metal pollution.

Several workers studied metal accumulation in different sparids such as in Acanthopagrus latus (Safahieh et al., 2013 and Yesser et al., 2013), Red striped sea bream and Black sea bream (El-Bahr and Abdelghany, 2015) and Acanthopagrus arabicus (Ahmed et al., 2016).

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6. Conclusion:

Present study discussed fishing gears, landing and export data of seventeen years which could help in regularising sustainable fisheries management practices in

Pakistan. Presented data for Length-weight relationship in male and female specimens of

Acanthopagrus arabicus showed variation in different seasons showing isometric, negative and positive allometric growth. The variation observed during this study may be due to feeding intensity in that particular season or gonadal cycle of the specie.

Current work suggested no significant relationship between condition factor

(K) and the gender of the species; the value of ‘K’ for male and female was more than 1 which indicates good condition of the fish. Length frequency distribution analysis suggested polymodal distribution in this fish and the modal length range was 216 mm to

232 mm.

Macroscopic and histological characters of testicular and ovarian zone of

Acanthopagrus arabicus in different maturity stages were provided. Observation suggested female Acanthopagrus arabicus were larger in size when attained 50 % maturity. Monthly variation recorded in mean gonadosomatic index values of male female

Acanthopagrus arabicus . Present study suggested spawning period of Acanthopagrus arabicus started in winter till beginning of spring. Standard ratio of 1:1 for male to female, examined by Chi-square test (p < 0.05) applied on Acanthopagrus arabicus .

Linear relationship showed increase in fecundity with increase of total length, body weight, gonad weight and length with significant coefficient of correlation. Present study also observed variation in number of ova found in anterior, middle and posterior parts of the right and left lobes of the ovary.

147

Food items found in stomach of Acanthopagrus arabicus were categorized into four groups, i.e. Teleost (different types of small fishes and Juveniles), Arthropods

(shrimps, prawns and crabs) Mollusks (bivalves, gastropods and cephalopods) and

Miscellaneous (unidentifiable food items, semi digested food and animal derivatives like: eggs, shells, scales, bones, eyes, fins, chela and other appendages etc.). Pattern of increase and decrease in Gastro-somatic Index was slightly different in both sexes of

Acanthopagrus arabicus and estimated Index of preponderance suggested that Teleost and

Arthropod groups closely related amongst male and female.

The results demonstrate that the meat and the gills of Acanthopagrus arabicus is an important source of calcium, potassium, magnesium and sodium. Some other trace elements were also were also estimated and observations showed difference in trace elements/metals concentrations amongst gills and meat in different months of the study.

However, Toxic elements such as Lead and Cadmium were not found in Acanthopagrus arabicus as samples run for detection. While Mercury (Hg) observed in very low concentration in both gills and meat. In present work several aspects along with life history processes (e.g. length-weight relationship, length frequency distribution, reproduction pattern, spawning, feeding habits etc.) are discussed which could help in fisheries management practices for commercially important fish Acanthopagrus arabicus in particular such as landing data, gear used for catch and export trends.

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7. Recommendations

Present findings may recommend Acanthopagrus arabicus to Fisheries management agencies of Pakistan as a suitable species for Aquaculture and export. As in present study it was observed this fish has considerable nutritional value for recommendation as a good source of food for people and aquaculture practices.

Moreover, further study of its population structure in the wild along with the data provided in this study could enhance stock assessment practices of this particular species. Because, fisheries are seen as a chance, a way to deliver the people, protein at a reasonable rate, to provide employment and enterprise which could alleviate poverty, to rise earnings of much-needed foreign exchange and contribute to the economy.

It is also recommended that, the Government of Pakistan identify the importance of the fisheries division to the state economy and the need for a well-articulated national plan to achieve the objective it has set for itself. The goal of the fisheries development strategy set forth in the perspective strategy is to rise production of fish, cope and conserve fisheries resources to withstand benefits to present and future generations, to encourage private enterprises, increase overall economic growth, and provide employment and incomes, particularly for the rural poor and unemployed youth.

In addition to this, researchers working on reproductive biology of hermaphrodite fishes can consider these suggestions. Such as, validate a macroscopic observation of the study (preferably with histology). Precise the macroscopic observations of maturity with the histological information as well. Observations should be made by taking into account specific methodological aspects for sequential hermaphrodite fish.

Development of management policy for the rational exploitation of Arabian yellow finned sea bream stock in the Arabian sea requires, in addition to the results obtained (growth, morphometric analysis and spawning biomass), information on stock– recruitment relationship, maximum sustainable yield and the corresponding level of fishing effort. As environmental conditions impact the various life-history stages of the exploited fish stock, information on the biotic and abiotic factors that affect the population dynamics and stock features of the Arabian yellow finned sea bream is necessary to outline the factors that cause alterations in stock size, growth and condition of Acanthopagrus arabicus in the Arabian Sea.

149

6. References

Abbas, G. (2000). Length weight and condition factor relationship of the Anchovy, Coilia Dussumieria and mullet Liza carinata from Bhanbhore back waters along Sindh Coast (Pakistan, Northern Arabian Sea). Pakistan J. Zool . 32 (3): 223 – 228.

Abdel-Baki, A.S., Dkhil, M.A. and Al-Quraishy, S. (2011). Bioaccumulation of some heavy metals in tilapia fish relevant to their concentration in water and sediment of Wadi Hanifah, Saudi Arabia. Afr. J. Biotechnol .10, 2541-2547.

Abol-Munafi, A. B., and UMEDA, S. (1994). The gonadal cycle of the yellowfin porgy, Acanthopagrus latus (Houttuyn) reared in the net cage at Tosa Bay, Japan. Aquacult. Sci. , 42 (1), 135-144.

Abou-Seedo, F., Dadzie, S., Al-Kanaan, K., & Sukumaran, J. V. (2003). Aspects of the reproductive biology of the hermaphroditic Yellowfin Seabream, Acanthopagrus latus (Hottuyn, 1782), in cages in Kuwait Bay. Zool. Middle East , 29 (1), 51-58.

Absar, A., Chadha, N. K., Joshi, K. D., Chakraborty, S. K., Sawant, P. B., Kumar, T., and Sharma, A. P. (2015). Maturation profile and fecundity of the exotic Oreochromis niloticus in the River Yamuna, India. J. Environ. Biol. 36 (4), 927-931.

Abu ‐Hakima, R. (1984). Some aspects of the reproductive biology of Acanthopagrus spp. (Family: Sparidae). J. Fish Biol. , 25 (5), 515-526.

Abu-Seedo, F.S. and AL-Khatib, H.Y. (1995). A histological and microscopic study of ovarian development in the grey mullet, Liza carinata (Valenciennes 1836). J. Uni. Kuwait (Science) 22, 239–254.

Adams, D. H., and McMichael, R. H. (2007). Mercury in king mackerel, Scomberomorus cavalla, and Spanish mackerel, S. maculatus, from waters of the south-eastern USA: regional and historical trends. Mar. Freshwater Res. , 58 (2), 187-193.

Adebiye, F. A. (2013). The sex ratio, gonadosomatic index, stages of gonadal development and fecundity of Sompat grunt, Pomadasys jubelini (Cuvier, 1830). Pakistan J. Zool , 45 (1), 41-46.

150

Adel, M. A. (2012). Effect of sex ratio on reproductive performance of broodstock Nile tilapia (Oreochromis niloticus) in suspended earthen pond hapas. Journal of the Arabian Aquaculture Society , 7(1), 19-28.

Agbugui, M. O. (2013). The sex ratio, gonadosomatic index, stages of gonadal development and fecundity of the grunt, Pomadasys jubelini (Cuvier, 1830) in the New Calabar-Bonny River. Rep. Opinion , 5(11), 31-37.

Agusa, T., Kunito, T., Yasunaga, G., Iwata, H., Subramanian, A., Ismail, A., and Tanabe, S. (2005). Concentrations of trace elements in marine fish and its risk assessment in Malaysia. Mar. pollut.bull. 51 (8-12), 896-911.

Ahmad, Q., Khan, D. and Yousuf, F. (2014). Length-weight relationship in adult Scomberomorus guttatus (Bloch. & Schneider, 1801) from Karachi coast, Pakistan. Intern. J. Biol. Research . 2(2): 101-107.

Ahmed, E. O., Ali, M. E. and Aziz, A. A. (2011). Length-weight Relationships and Condition factors of six fish species in Atbara River and Khashm el- girba Reservoir, Sudan. Int. J. Agric. Sci. 3 (1): 65-70.

Ahmed, Q., Bat, L., Yousuf, F., and Arıcı, E. (2016). Heavy metals in Acanthopagrus arabicus Iwatsuki, 2013 from Karachi coasts, Pakistan and potential risk of human health. Int. j. fish. aquat. 4(1), 203-208.

Ahmed, Q., Khan, D. and Yousuf, F. (2015). Interrelationships of fresh body weight and total body length and condition factor in adult Pomadasys stridens (Forrskal, 1775) (Family Pomadasyidae) from Karachi, Pakistan. FUUAST J. Biol . 5(1): 161 – 168.

Ahmed, Q., Tabbassum, S., Younus, F. and Türkman, M. (2013). Length-weight relationship amd seasonal distribution of Megalaspis cordylla (Linnaeus 1758) fish size frequency variation, Karachi Coast. Fen Bilimeiri Desgisi / the Black Sea J. Sci . 31(9): 115123.

Akhtar, N. (2010). Enterprises Based Fisheries Sector: Study and Strategic Plan for Interventions at Enterprises Level to Enhance Quality Production. UNIDO (TRTA II)

151

Akoto, O., Bismark Eshun, F., Darko, G., and Adei, E. (2014). Concentrations and health risk assessments of heavy metals in fish from the Fosu Lagoon. Int. J. Environ. Res. 8(2), 403-410.

Al-Busaidi, M., Yesudhanon, P., Al-Mughairi, S., Al-Rahbi, W. A. K., Al-harthy, K. S., Al-Mazrooei, N. A. and AlHabsi, S. H. (2011). Toxic metals in commercial marine fish in Oman with reference of national and international standards. Chemosphere , 85, 67–73.

Al-Hussani, A.H. (1949). On the fictional morphology of the alimentary tract of some fishes in relation to difference in their feeding habits, Anatomy History. Q. J. Microsc. Sci . 92:190-240.

Ali, S. S. (1979). Age, growth and length weight relationship of the roach Rutilus rutilus L. Llyn Tegid, North Wales . Pakistan J. Zool , 11 (1), 1-19.

Al-Kiyumi, F. R. (2013). Biology and fisheries assessment of the Arabian pandora (pagellus affinis ) (Boulenger, 1887) in the Arabian Sea, Sultanate of Oman (Doctoral dissertation, University of Tasmania).

Allison, M. E. (2011). The Fecundity, Gonadosomatic and Hepatosomatic Indicies of Pellonula Leonensis in the Lower Nun River, Niger Delta, Nigeria. Curr. Res. J. Biol. Sci . 3(3), 175-179.

Allsop, D. J., and West, S. A. (2004). Sex ‐ratio evolution in sex changing animals. Evolution , 58 (5), 1019-1027.

Al-Majed, N. B., and Preston, M. R. (2000). An assessment of the total and methyl mercury content of zooplankton and fish tissue collected from Kuwait territorial waters. Mar. Pollut. Bull . 40 (4), 298-307.

Alonso-Fernández, A., Alós, J., Grau, A., Domínguez-Petit, R., and Saborido-Rey, F. (2011). The use of histological techniques to study the reproductive biology of the hermaphroditic Mediterranean fishes Coris julis , Serranus scriba , and Diplodus annularis . Mar. Coast. Fish . 3(1), 145-159.

Amtyaz, M., Khan, M. Z., and Hashmi, M. U. A. (2014). The sex ratio, gonadosomatic index and stages of gonadal development of saddle grunt fish, Pomadasys

152

maculatum (bloch, 1793) of Karachi coast. Canadian Journal of Pure and Applied Sciences , 8(1), 2721-2726.

Andem, A. B., George, U. U., & Eyo, V. O. (2013). Length Frequency Distribution of (Chrysichthys nigrodigitatus ) (Lecepede, 1803) (Chrysichthys, Bagridae) from Itu Head Brigde. Int. J. Sci. Res . 2, 258-260.

Araújo, F. G., Andrade, C. C., Santos, R. N., Santos, A. F. G., and Santos, L. N. (2005). Spatial and seasonal changes in the diet of Oligosarcus hepsetus (Characiformes, Characidae) in a Brazilian reservoir. Braz. J. Biol. 65 (1), 1-8.

Arora, R., and Julka, J. M. (2017). Comparative analysis of morphometric characters between artificial and natural stocks of endangered golden mahseer, Tor putitora (hamilton) population from Himachal Pradesh, India. Int. J. Plant Anim. Environ. Sci . 7(3), 19-25.

Atz, J.W. (1964). Intersexuality in fishes. In: Armstrong CN, Marshall AJ (eds) Intersexuality in vertebrates including man. Academic Press, London , pp 145-239.

Ayo-Olalusi, C. I. (2010). Organoleptic characteristics, length-weight relationship and condition factor of Oreochromis niloticus in Egah River at idah lga of kogi state, nigeria. Inter. J. Food Saf. 12, 62-70.

Babare, R. S., Chavan, S. P., and Kannewad, P. M. (2013). Gut Content Analysis of Wallago attu and Mystus (Sperata) seenghala The Common Catfishes from Godavari River System in Maharastra State. Adv. biores . 4(2), 123-128.

Bagenal, T. B., and Tesch, A. T. (1978). Conditions and growth pattern in freshwater habitats. Oxford: Blackwell Scientific publishing . pp. 75-89.

Bahuguna, S. N., and Khatri, S. (2009). Studies on fecundity of a Hill stream loach Noemacheilus montanus (McClelland) in relation to total length, total weight, ovary length and ovary weight. Our Nature , 7(1), 116-121.

Batista, M. I., e Costa, B. H., Gonçalves, L., Henriques, M., Erzini, K., Caselle, J. E. and Cabral, H. N. (2015). Assessment of catches, landings and fishing effort as useful tools for MPA management. Fish. Res. 172 , 197-208.

Begg, G., Friedland, K. D. and Pearce, J. B. (1999). Stock identification-its role in stock assessment and fisheries management. Fish. Res. 43, 1–8.

153

Belova, G. V., and Viktorovskaya, G. I. (2007). Morphometric characteristic of sex cells and seasonal changes of female gonads of Cucumaria japonica (Semper, 1868) (Echinodermata: Holothuroidea) from Peter the Great Bay, Sea of Japan. Russ. J. Mar. Biol. 33 (3), 173.

Beverton, R.J.H. and HOLT, S.J. (1957). On the dynamics of exploited fish populations. Fish, Invest. Land . (2) 19: 533 pp.

Bhatnagar, G. K., and Karamchandani, S. J. (1970). Food and feeding habits of Labeo fimbriatus (Bloch) in river Narmada near Hoshangabad (MP). J. Inland Fish. Soc. India , 2, 30-50.

Biddinger, G. R. and Gloss, S. P. (1984). The importance of trophic transfer in the bioaccumulation of chemical contaminants in aquatic ecosystems. Residue Rev . 91:103–145

Bolger, T., and Connolly, P. L. (1989). The selection of suitable indices for the measurement and analysis of fish condition. J. Fish Biol. 34(2), 171-182.

Booth, A.J. and Buxton, C.D. (1997). The biology of the panga, Pterogymnus laniarius (Teleostei: Sparidae), on the Agulhas Bank, South Africa. Environ. Biol. Fish 49, 207–226.

Bose, S., Al-Masroori, H. S., and Al-Habsi, A. M. H. A. (2017). Traditional fisheries enforcement program: A case of three coastal villages in the eastern part of Oman. Marine Policy , 78 , 61-67.

Brraich, O. S., and Akhter, S. (2015). Morphometric characters and meristic counts of a fish, Crossocheilus latius latius (Hamilton-Buchanan) from Ranjit Sagar Wetland, India. Int. J. Fish. Aquat. Stud. 2(5), 260-265.

Buckland, A., Baker, R., Loneragan, N., and Sheaves, M. (2017). Standardising fish stomach content analysis: The importance of prey condition. Fish. Res. 196 , 126- 140.

Bury, N.R., Walker, P.A. and Glover, C.N. (2003). Nutritive metal uptake in teleost fish. J Exp Biol. 206:11–23.

154

Butler, G. L., and Wooden, I. J. (2012). Dietary habits of a large, long-lived endangered Australian percichthyid, the eastern freshwater cod Maccullochella ikei . Endanger. Species Res. 16 (2), 199-209.

Buxton, C.D. and Garratt, P.A. (1990). Alternative reproductive styles in seabreams (Pisces: Sparidae). Envir. Biol. Fish. 28: 113-124.

Cadrin SX, Friedland KD, Waldman JR (2005). Stock identification methods—an overview. In: Cadrin SX, Friedland KD, Waldman JR (eds) Stock identification methods. Elsevier Academic Press , UK, pp 3–6.

Cadrin, S. X. (2000). Advances in morphometric identification of fishery stocks. Rev. Fish boil. Fisher. 10 (1), 91-112.

Canli, M., and Atli, G. (2003). The relationships between heavy metal (Cd, Cr, Cu, Fe, Pb, Zn) levels and the size of six Mediterranean fish species. Environ. Pollut. 121 (1), 129-136.

Chen, M. H. (2002). Baseline metal concentrations in sediments and fish, and the determination of bioindicators in the subtropical Chi-ku Lagoon, SW Taiwan. Mar. Pollut. Bull. 44 (7), 703-714.

Cheng, Q. Q., Lu, D. R., and Ma, L. (2005). Morphological differences between close populations discernible by multivariate analysis: a case study of genus Coilia (Teleostei: Clupeiforms). Aquat. Living Resour. 18 (2), 187-192.

Chételat, J., Cloutier, L., and Amyot, M. (2013). An investigation of enhanced mercury bioaccumulation in fish from offshore feeding. Ecotoxicology , 22 (6), 1020-1032.

Clark, F. N.(1928). The weight–length relationship of the California sardine ( Sardina caerulea ) at San Pedro. Division of Fish and Game, Fish Bull . No. 12. 59 pp.

Collignon, J. (1960). Contribution à la connaissance des Otolithus des côtes d'Afrique Equatoriale. Bulletin de l'Institut d'Etudes Centrafricaines , (19-20), 55-84.

Costa, J. L., de Almeida, P. R., and Costa, M. J. (2003). A morphometric and meristic investigation of Lusitanian toadfish Halobatrachus didactylus (Bloch and Schneider, 1801): evidence of population fragmentation on Portuguese coast. Scientia Marina , 67 (2), 219-231.

155

Costa, M. R. D., and Araújo, F. G. (2003). Length-weight relationship and condition factor of Micropogonias furnieri (Desmarest) (Perciformes, Sciaenidae) in the Sepetiba Bay, Rio de Janeiro State, Brazil. Revista Brasileira de Zoologia , 20(4), 685-690.

Coward, K., and Bromage, N.R. (1998). Histological classification of oocyte growth and the dynamics of ovarian recrudescence in Tilapia zillii. J. Fish Biol . 53, 285–302.

Cronin-Fine, L., Stockwell, J. D., Whitener, Z. T., Labbe, E. M., Willis, T. V., and Wilson, K. A. (2013). Application of morphometric analysis to identify alewife stock structure in the Gulf of Maine. Mar. Coast. Fish. 5(1), 11-20.

Cunha, N. L., Catella, A. C., & Kinas, M. A. (2007). Growth parameter estimates for a small fish of the Pantanal Brazil: Moenkhausia dichroura (Characiformes, Characidae). Braz. J. Biol. 67, 293-297.

Dan-Kishiya, A. S. (2013). Length-weight relationship and condition factor of five fish species from a tropical water supply reservoir in Abuja, Nigeria. Am. J. Res. Commun . 1(9), 175-187.

Darlina, M. N., Masazurah, A. R., Jayasankar, P., Jamsari, A. F. J., and Siti, A. M. (2011). Morphometric and molecular analysis of mackerel (Rastrelliger spp) from the west coast of Peninsular Malaysia. Genet. Mol. Res. 10(3), 2078-2092.

Deepti, V. A., and Sujatha, K. (2017). Studies on length frequency distribution, length- weight relationship and some aspects of reproductive biology of Katsuwonus pelamis (Linnaeus, 1758) off north Andhra Pradesh, central eastern coast of India. Indian J. Mar. Sci. 46(11), 2295-2302.

Dia, M., Ghorbel, M., Bouain, A. and Kone, Y. (2000). Diet of Pagrus caeruleostictus (Sparidae) of Nouakchott coasts (Mauritania). Cybium .24:81–88.

Doha, S. and Hye, M.A. (1970). Fecundity of the Padma river Hilsa ilisha (Ham.). Pak. J. Sci ., 22: 176-183.

Doherty, D., and McCarthy, T. K. (2004, May). Morphometric and meristic characteristics analyses of two western Irish populations of Arctic Char, Salvelinus alpinus (L.). In Biology and Environment: proceedings of the Royal Irish Academy (pp. 75-85). Royal Irish Academy.

156

Dourado, O. F., and Davies, W. D. (1978). Length-weight relationships and condition indices of fishes from reservoirs of Ceará, Brazil.

Duffy, D.C. and Jackson, S. (1986). Diet studies of seabirds: a re- view of methods. Colon Waterbirds 9: 1 −17 .

Dul čić, J., and Kraljevi ć, M. (1996). Weight-length relationships for 40 fish species in the eastern Adriatic (Croatian waters). Fish. Res. 28 (3), 243-251.

Dwivedi, A. K., and Dubey, V. K. (2013). Advancements in morphometric differentiation: a review on stock identification among fish populations (Retraction of vol 23, pg 23, 2013). Rev. Fish Biol. Fisher. 23 (4), 557-557.

El Sayed, A. F. M., and Abdel-Bary, K. (1993). Population biology of sparid fishes in Qatari waters 2. Age, growth and mortality of black-banded bream, Mylio bifasciatus (forsskal). Qatar Univ. Sci. J. 13(2): 348-352.

Elahi, N., Yousuf, F., Tabassum, S. and Baloch, W. A. (2016). Seasonal variation in Length-weight relationship and condition factor of Indian oil sardine Sardinella longiceps (Valenciennes, 1847) from Baluchistan coast. Sindh Univ. Res. Jour, (Sci. Ser.) . vol 48 (1) 113 – 116.

El-Bahr, S. M., and Abdelghany, A. (2015). Heavy metal and trace element contents in edible muscle of three commercial fish species, and assessment of possible risks associated with their human consumption in Saudi Arabia. J. Adv. Vet. Anim. Res . 2(3), 271-278.

Eschmeyer, W.N. (Ed.) (2013). Catalog of fishes: genera, species, references. Available from: http://research.calacademy.org/research/icthyology/catalog/fishcatmain.asp

Fagade, S.O. (1978). Observation of the biology of two species of Tilapia from the Lagos lagoon Nigeria. Bull Inst Fond Afr Nore (Ser. A) 41:627-658.

Fairclough, D. V., Hesp, S. A., Potter, I. C., and Hall, N. G. (2004). Determination of the biological parameters required for managing the fisheries of four tuskfish species and western yellowfin bream. FRDC project 2000/137.

FAO (2009). The state of world fisheries and aquaculture 2008. Rome (Italy): FAO Fisheries Department. 162 p.

157

FAO (Food and Agriculture Organization). The food consumption refers to the amount of food available for human consumption as estimated by the FAO Food Balance Sheets, 2010.

FAO/WHO. (2011). Joint FAO/WHO food standards program codex committee on contaminants in food, 5th session, the Netherland. 21-25th March 2011.

Fehri-Bedoui, R., and Gharbi, H. (2008). Sex-ratio, reproduction and feeding habits of Pomadasys incisus (Haemulidae) in the Gulf of Tunis (Tunisia). Acta Adriatica: Int. J. Mar. Sci. 49 (1), 5-19.

Flammang, B. E., Ebert, D. A., and Cailliet, G. M. (2008). Reproductive biology of deep- sea catsharks (Chondrichthyes: Scyliorhinidae) in the eastern North Pacific. Environ. Biol. Fishes , 81 (1), 35-49.

Food Composition Table for Pakistan. (2001). Department of Agricultural Chemistry NWFP, Ministry of Planning and Development Government of Pakistan Islamabad.

Fowler, A.J., McLeay, L.J. and Short, D.A. (2000). Spatial variation in size and age structure and reproductive characteristic of the King George whiting (Percoidei: Sillaginidae) in South Australian waters. Mar. Freshwater Res . 51, 11–22.

French, B., Potter, I. C., Hesp, S. A., Coulson, P. G., and Hall, N. G. (2014). Biology of the harlequin fish Othos dentex (Serranidae), with particular emphasis on sexual pattern and other reproductive characteristics. J. Fish Biol. 84 (1), 106-132.

Froese, R. (2006). Cube law, condition factor and weight–length relationships: history, meta ‐analysis and recommendations. J. Appl. Ichthyol . 22 (4), 241-253.

Gerking, S.D. (1994). Feeding ecology of fish. Academic Press, San Diego, CA. 416 pp.

Goldhaber, S., (2003). Trace element risk assessment: Essentiality vs. toxicity. Regul. Toxicol. Pharm. 38, 232–242.

Gomon, M.F., Glover, J.C.M. and Kuiter, R.H. (1994). The fishes of Australia’s South Coast. Flora and Fauna of South Australia Handbooks Committee (eds.). State Print, Adelaide . 992 p.

158

Gordon, A. K., and Bills, I. R. (1999). Aspects of the feeding and reproductive biology of the Lake Tanganyikan cichlid, Lamprologus ornatipinnis (Pisces, Cichlidae). Environ. Biol. Fishes. 55 (4), 431-441.

Grimes CB, Johnson AG, Fable WA Jr (1987). Delineation of king mackerel (Scomberomorus cavalla ) stocks along the US east coast and in the Gulf of Mexico. In: Kumpf HE, Vaught RN, Grimes CB, Johnson AG, Nakamura EL (eds) Proceedings of the stock identification workshop. NOAA technical memorandum NMFS-SEFC , vol 199, pp 186–187

Gundersen, A. C., Stenberg, C., Fossen, I., Lyberth, B., Boje, J., and Jørgensen, O. A. (2010). Sexual maturity cycle and spawning of Greenland halibut Reinhardtius hippoglossoides in the Davis Strait. Journal of fish biology , 77 (1), 211-226.

GWO, H. H. (2008). Morphology of the fertilizable mature egg in the Acanthopagrus latus , A. schlegeli and Sparus sarba (Teleostei: Perciformes: Sparidae). Journal of microscopy , 232 (3), 442-452.

Hajisamae, S., Chou, L.M. and Ibrahim, S. (2003). Feeding habits and trophic organization of the fish community in shallow waters of an impacted tropical habitat. Estuar. Coast. Shelf Sci . 58: 89–98.

Hameed, L., Habib-ul-Hasan, Khan, M.Z. and Asim, M. (2013). Length-weight relationship in common Sea bream Acanthopagrus berda (Forsskål 1775) from Karachi coast, Pakistan. Int. J. Biol. & Biotech . 10(4): 593-596.

Hanel, R. and Sturmbauer, C. (2000). Multiple recurrent evolution of trophic types in northeastern Atlantic and Mediterranean seabreams (Sparidae, Percoidei). J. Mol. Evol . 50, 276– 283.

Hartvig, M. (2011). Ecological processes yield complex and realistic food webs. In: Food Web Ecology - individual life-histories and ecological processes shape complex communities, pp. 75 - 126. ISBN 978-91-7473-080-7. Ph.D. thesis, Department of Biology, Lund University, Sweden.

Hassanien, H. A., Kamel, E. A., Salem, M. A., and Dorgham, A. S. (2011). Multivariate analysis of morphometric parameters in wild and cultured Nile Tilapia, Oreochromis niloticus . Journal of the Arabian Aquaculture Society , 6(2), 424-440.

159

Havelange, S., Lepoint, G., Dauby, P., and Bouquegneau, J. M. (1997). Feeding of the sparid fish Sarpa salpa in a seagrass ecosystem: diet and carbon flux. Mar. Ecol. 18(4), 289-297.

Hedayati, A., Safahieh, A., Savari, A., and Ghofle, J. (2011). Detection of range finding test of mercury chloride in yellow-fin sea bream ( Acanthopagrus latus ). Transylv. Rev. Syst. Ecol. Res . (12), 125-134.

Hedayati, A., Safahieh, A., Savari, A., and Marammazi, J. G. (2010). Detection of Range Finding Test of Mercury Chloride in Yellowfin Sea Bream ( Acanthopagrus latus ). Iran J. Energy Environ . 1(3), 228-233.

Hesp, S.A., Potter, I.C. and Hall, N.G. (2004). Reproductive biology and protandrous hermaphroditism in Acanthopagrus latus . Environ. Biol. Fish . 70, 257–272.

Heupel, M.R., Williams, A.J., Welch, D.J., Davies, C.R., Penny, A., Kritzer, J.P., Marriott, R.J. and Mapstone, B.D. (2010). Demographic characteristics of exploited tropical lutjanids: a comparative analysis, Fish. Bull . 108, 420-432.

Horinouchi, M., Tongnunui, P., Furumitsu, K., Nakamura, Y., Kanou, K., Yamaguchi, A. and Sano, M. (2012). Food habits of small fishes in seagrass habitats in Trang, southern Thailand. Fisheries Sci. 78(3), 577-587.

Hoseinzade, M., Imanpoor, M. R., Aghilinejhad, S. M., and Shabany, A. (2012). Histology of Ovarian Development and Investigated Some Biological Aspects of Persian Sturgeon, Acipenser percicus , in Caspian Sea Iran. World Appl. Sci. J. 18(9), 1198- 1202.

Hossain, M. A., Nahiduzzaman, M., Saha, D., Khanam, M. U. H., and Alam, M. S. (2010). Landmark-based morphometric and meristic variations of the endangered Carp, Kalibaus Labeo calbasu , from stocks of two isolated rivers, the Jamuna and Halda, and a hatchery. Zool. Stud. 49(4), 556-563.

Hossain, M. S., and Sultana, N. (2016). Morphometric characters and length-weight relationship of Bele, (Glossogobius giuris ) from Mithamoin haor, Kissorgonj, Bangladesh. J. Bangladesh Agril. Univ. 12(2), 389-395.

160

Hughes, J. M., and Stewart, J. (2006). Reproductive biology of three commercially important Hemiramphid species in south-eastern Australia. Environ. Biol. Fishes . 75(2), 237-256.

Hung, T. C., Huang, C. C., Meng, P. J., Chuang, A., and Wu, S. J. (1999). Heavy metals in fish tissues and different species of fish from the southern coast of Taiwan. Chem. Ecol. 16(4), 283-296.

Hunter, J. R. (1992). Fecundity, spawning and maturity of female Dover sole Microstomus pacificus , with an evaluation of assumption and precision. Fish. Bull. , 90, 101-128.

Husain, S. (2014). National Plan of Action for Conservation and Management of Sharks. WWF. Community based Fisheries Management, 2010. Development of Pakistan.

Hussain, N. A., and Abdullah, M. A. S. (1980). Length-weight relationship, spawning season and food habits of six commercial fishes in Kuwaiti waters. Indian journal of fisheries . 24(1/2), 181-194.

Hussain, S. M., Paperno, R. and Khatoon, Z. (2010). Length–weight relationships of fishes collected from the Korangi-Phitti Creek area (Indus delta, northern Arabian Sea). J. Appl. Ichthyol . 26, 477–480.

Hynes, H. B. N. (1950). The food of fresh-water sticklebacks ( Gasterosteus aculeatus and Pygosteus pungitius ), with a review of methods used in studies of the food of fishes. J. Anim. Ecol. 36-58.

Il’insky, E. N., and Kuznetsova, N. A. (2010). Spatial and length distribution, sex composition, and feeding of the notched-fin eelpout Zoarces elongatus (Perciformes: Zoarcidae) in the Sea of Okhotsk. Russ. J. Mar. Biol . 36(4), 252- 257.

Isajlovic, I., Vrgoc, N., Zorica, B., Peharda, M., Krstulovic-Sifner, S., and Piccinetti, C. (2009). Age, growth and length-weight relationship of Coelorinchus caelorhincus (Risso, 1810) in the Adriatic Sea. Acta Adriatica , 50(1), 23-30.

Iwatsuki, Y. (2013). Review of the Acanthopagrus latus complex (Perciformes: Sparidae) with descriptions of three new species from the Indo-West Pacific Ocean. J. Fish Biol. 83: 64-95.

161

Jaiswar, A.K., Parida, P.K., Chakraborty, S.K. and Palaniswamy, R. (2004). Morphometry and length-weight relationship of obtuse barracuda Sphyraena obtusata (Cuvier) (Teleostomi/Actinopterygii/Sphyraenidae) from Bombay waters, west coast of India. Indian J. Mar. Sci ., 33(3), 307-309.

Jalbani, S., Narejo, N., Jalbani, Y., and Iqbal, R. (2014). Morphometric characters and their relationship in relation total length in Cirrhinus reba (Hamilton) from Manchar Lake, District Jamshoro, Sindh, Pakistan. Sindh University Research Journal (Science Series) , 46 (2).

Jan, M., Jan, U., and Shah, G. M. (2014). Studies on fecundity and Gonadosomatic index of Schizothorax plagiostomus (Cypriniformes: Cyprinidae). J. Threat. Taxa . 6(1), 5375-5379.

Jarvinen, A.W. and Ankley, G. T. (1999). Linkage of effects to tissue residues: development of a comprehensive database for aquatic organisms exposed to inorganic and organic chemicals. SETAC Press. Pensacola , Florida, pp 1–358.

Jennings, S., Reynolds, J.D. and Mills, S.C. (1998). Life history correlates of responses to fisheries exploitation. Proc. R. Soc. Lond. Ser. B, Biol. Sci . 265, 333–339.

Jensen, P. T., and Hyde, J. (1971). Sex ratios and survival estimates among salmon populations. Calif. Fish Game , 57 (1), 90-98.

Jeong, M. H., Lim, H. K., Kim, Y. S., Kim, S. Y., and Chang, Y. J. (2010). Sperm Collection Time, Sex Steroid Hormones, and Gonadal Development of Black Porgy, Acanthopagrus schlegeli , acclimated in Freshwater. Korean J. Fish. Aquat. Sci . 43(5), 474-481.

June, F. C. (1953). Spawning of yellowfin tuna in Hawaiian waters. US. Fish. Wildl. Serv. Fish. Bull ., 54: 47-64.

Juras, A. A., and Yamaguti, N. (1989). Sexual maturity, spawning and fecundity of king weakfish Macrodon ancylodon , caught off Rio Grande do Sul State (southern coast of Brazil). Boletim do Instituto Oceanográfico , 37 (1), 51-58.

Kadharsha, K., Mohanchander, P., Lyla, P. S., and Khan, S. A. (2013). Feeding and Reproductive Biology of Saurida undosquamis (Richardson, 1848) from Parangipettai Coast, Southeast Coast of India. Pak. J. Biol. Sci . 16(22), 1479-1487.

162

Kallianiotis, A., Torre, M. and Argyri, M. (2005). Age, growth, mortality, reproduction, and feeding habits of the striped seabream, Lithognathus mormyrus (Pisces: Sparidae), in the coastal waters of the Thracian Sea, Greece. Sci. Mar . 69:391–404.

Kappus, S. M. (2012). The influence of population density and sex ratio on reproduction and sex change of a temperate reef fish , Lythrypnus dalli (Doctoral dissertation, UCLA).

Karaseva, E. M., Patokina, F. A., and Kalinina, N. A. (2013). Fish eggs and larvae in the diet of herring Clupea harengus membras Linnaeus, 1758 and the sprat Sprattus sprattus balticus (Schneider, 1904) (Clupeidae) in the Southeastern Baltic Sea. Russ. J. Mar. Biol . 39(5), 350-356.

Kefi, A. S., Kang'ombe, J., Kassam, D., and Katongo, C. (2012). Growth, Reproduction and Sex Ratios in Oreochromis Andersonii (Castelnau, 1861) Fed with Varying Levels of 17 α-Methyl Testosterone. J. Aquac. Res. Dev . 3(8).

Kesteven, G.L. (1996). A fisheries science approach to problems of world fisheries or: three phases of an industrial revolution. Fish. Res. 25(1): 5-18.

Keymaram, F., Hosseini, S., Darvishi, M., Talebzadeh, S. A., and Sadeghi, M. S. (2010). Reproduction and spawning patterns of the Scomberomorus commerson in the Iranian coastal waters of the Persian Gulf & Oman Sea. Iran. J. Fish. Sci. 9(2), 233-244.

Khan, M. A. Amtayaz and Siddiqui, S. (2013). Length-weight relationship in Pomadasys maculatus (Bloch) from Karachi coast, Pakistan. Int. J. Biol. Biotech , 10(3), 471- 474.

Khan, M. A. and Hoda, S. M. S. (1993). Sex ratio of the Euryglossa orientalis (Bl. & Schn.) (Family: Soleidae) from the Karachi coast . Pak. J. Mar. Sci . 2:157-159.

Khan, M. A., Yousuf, K., and Riaz, S. (2013). Observations on sex ratio and fecundity of Sillago sihama (Forsskal, 1775) (Family; Sillaginidae) from Karachi Coast. J. Entomol. Zool. Stud. 1, 152-157.

Khan, M. A., Yousuf, K., and Riaz, S. (2014). Food and Feeding Habits of Sillago sihama (Forsskal, 1775) (Family: Sillaginidae) from Karachi Coast. Int. J. Fauna Biol. 1(3), 27-31.

163

Khan, M., and Hoda, S. M. S. (1993). Observation on the food and feeding habits of Euryglossa orientalis (Bl. and Schn) (family: Soleidae) from Karachi Coast. Journal of Islamic Academy of Sciences , 6(3), 185-188.

Khan, M.A. and Hoda, S.M.S. (1998). Some aspects of reproductive biology of Euryglossa orientalis (Bl. & Schn.) in North Arabian Sea along the coast of Karachi, Pakistan. Turkish J. Zool ., 22: 241-249.

Khan, M.A. and Hoda, S.M.S. (1997) Allometric study of skeleton weight, body weight and length relationship of Euryglossa orientalis (Bl. & Schn.) (Family: Soleidae) from Karachi coast. Pak. J. Mar. Sci . 6(1-2), pp. 93-97.

Khatoon, Z., Paperno, R. and Hussain, S. M. (2014). Length-weight relationship of five fish species collected from Manora Channel and associated backwaters of the northern Arabian Sea. J. Appl. Ichthyol . 30, 235 – 238.

Khawar, M., Kalsoom, R., Masood, Z., Hasan, Z., Iqbal, F., and Razzaq, W. (2015). Length-weight relationship, condition and relative condition parameters of Mugilincilus (Mugilidae: Mugiliformes) collected from the River Indus of district Sukkur, Pakistan. In Biol. Forum (Vol. 7, No. 1, p. 793). Research Trend.

Khoshnood, Z., Khoshnood, R., Mokhlesi, A., Ehsanpour, M., and Afkhami, M. (2012). Determination of Cd, Pb, Hg, Cu, Fe, Mn, Al, As, Ni and Zn in important commercial fish species in northern of Persian Gulf. J. Cell Anim. Biol . 6(1), 1-9.

Khumar, F., and Siddiqui, M. S. (1991). Length-weight relationship of the carp, Puntius sarana Ham. of a reservoir and three riverine ecosystems in north India. J. Freshwat. Biol . 3(1), 81-88.

King, M. (2007). Fisheries biology, assessment and management. 2nd Ed. Oxford: Blackwell Scientific Publications , pp. 1-381.

Kingdom, T. and Allison, M. E. (2011). The Fecundity, Gonadosomatic and Hepatosomatic Indicies of Pellonula Leonensis in the Lower Nun River, Niger Delta, Nigeria. Curr. Res. J. Biol. Sci. 3(3), 175-179.

Kingsford, M. J., and Gray, C. A. (1996). Influence of pollutants and oceanography on abundance and deformities of wild fish larvae. In Detecting Ecological Impacts (pp. 235-255).

164

Kjesbu, O.S., Solemdal, P., Bratlan, P. and Fonn, M. (1996). Variation in annual egg production in individual captive Atlantic cod (Gadus morhua). Can. J. Fish. Aquat. Sci . 53, 610–620.

Kosai, P., Sathavorasmith, P., Jiraungkoorskul, K., and Jiraungkoorskul, W. (2014). Morphometric characters of Nile tilapia ( Oreochromis niloticus ) in Thailand. Walailak J. Sci. & Tech . 11(10), 857-863.

Krug, H. (1998). Variation in the reproductive cycle of the blackspot seabream, Pagellus bogaraveo (Brünnich, 1768) in the Azores. ARQUIPÉLAGO. Life and Marine Sciences , 16 , 37-47.

Kumar, B., Sajwan, K. S., and Mukherjee, D. P. (2012). Distribution of Heavy Metals in Valuable Coastal Fishes from North East Coast of India. Turkish Journal of Fisheries and Aquatic Sciences. 12: 81-88 (2012).

Kumar, K. H., and Kiran, B. R. (2016). Relative Condition Factor of Feather Back, Notopterus Notopterus (Pallas) from Jannapura Pond, Bhadravathi Taluk, Karnataka. IJSRSET , 2(1), 36-39

Laevastu, T. (1965). Manual of Methods in Fisheries Biology. FAO, Rome . 51 pp.

Lambert, Y., Yaragina, N.A., Kraus, G., Marteinsdottir, G., Wright, P. (2003). Using environmental and biological indices as proxies of egg and larval production of marine fishes. J. Northw. Atl. Fish. Sci . 33, 115–159.

Lammens, E. H., van Nes, E. H., Meijer, M. L., and van den Berg, M. S. (2004). Effects of commercial fishery on the bream population and the expansion of Chara aspera in Lake Veluwe. Ecological modelling , 177(3-4), 233-244.

Le Cren, E. D. (1951). The length-weight relationship and seasonal cycle in gonad weight and condition in the perch ( Perca fluviatilis ). The Journal of Animal Ecology , 201- 219.

Lee, M. F., Huang, J. D., and Chang, C. F. (2008). Development of ovarian tissue and female germ cells in the protandrous black porgy, Acanthopagrus schlegeli (Perciformes, Sparidae). Zool stud , 47 , 302-316.

Lima-Junior, S. E., and Goitein, R. (2001). A new method for the analysis of fish stomach contents. Acta scientiarum , 23 (2), 421-424.

165

Maddock, D. M. and Burton, P. M. (1999). Gross and histological observations of ovarian development and related condition changes in American plaice . J Fish Biol 53:928–944.

Mahmood, K., Ayub, Z., and Siddiqui, G. (2011). Sex-ratio, maturation and spawning of the Indian ilisha, ilisha melastoma (clupeiformes: pristigasteridae) in coastal waters of Pakistan (northern Arabian Sea). Indian J. Mar. Sci. 40(4), 516-524.

Mahmood, K., Ayub, Z., Moazzam, M. and Siddiqui, G. (2012). Length– weight relationship and condition factor of Ilisha melastoma (Clupeiformes: Pristigasteridae) o ff Pakistan. Pak. J. Zool . 44, 71–77.

Mahmoud, H. H. (2009). Gonadal maturation and histological observations of Epinephelus areolatus and Lethrinus nebulosus in Halaieb/Shalatien Area “Red Sea”, Egypt. Global Veterinaria , 3(5), 414-423.

Mahmoud, U. M., El-Gammel, F. I., Mehanna, S. F. and El-Mahdy, S. M. (2016). Study on Morphometric and Meristic Characters of Acanthopagrus bifasciatus (Forsskål, 1775) from Southern Red Sea, Egypt. International Journal of Science and Research. 5(1), 1735-1739.

Maji, D., Pradhan, A., Bhattacharya, S., and Mahapatra, B. K. (2016). Morpho-meristic characteristics of a rare species Synaptura commersonnii (Lacepède, 1802) from North-East coast of India, West Bengal. Int. J. Fish. Aquat. Stud. 4(5), 237-241.

Mariani, S., Maccaroni, A., Massa, F., Rampacci, M. and Tancioni, L. (2002). Lack of consistency between trophic interrelationships of five sparid species in two adjacent Mediterranean coastal lagoons. Journal of Fish Biology , 61, 138-147.

Marriott, R. J., Mapstone, B. D. and Begg, G. A. (2007). Age-specific demographic parameters, and their implications for management of the red bass, Lutjanus bohar (Forsskal 1775): a large, long-lived reef fish. Fish. Res . 83(2-3), 204–215.

Mathews, C.P., Al-Mamry, J. and Al Habsy, S. (2001). Precautionary management of Oman ‟s demersal fishery. In: Goddard, S., Al Oufi, H., McIlwain, J., Claereboudt, M. (eds.). Proceedings of the 1st International Conference on Fisheries, Aquaculture and Environment in the Northwest Indian Ocean, 2001. Sultan Qaboos University, Muscat, Sultanate of Oman, pp. 29–38.

166

Mathialagan, R., Sivakumar, R., Rajasekaran, N., and Chandrasekar, S. (2014). Length– frequency distribution and length-weight relationship of reba carp Cirrhinus reba (Hamilton, 1822 Cypriniformes: Cyprinidae) from Lower Anicut, Tamil Nadu, India. International Journal of Fisheries and Aquatic Studies 2(2): 115-125

McDonough, C.J., Roumillat, W.A. and Wenner, C.A. (2003). Fecundity and spawning season of striped mullet ( Mugil cephalus ) in South Carolina estuaries. Fish Bull . 101(4), 822–834.

Mehanna, S. F., El-Gammal, F. I., Usama, Mahmoud, U. M. and El-Mahdy, S. M. (2017). Food and Feeding Habits of Two-Bar Seabream, Acanthopagrus bifasciatus (Forsskål, 1775) from Southern Red Sea, Egypt. Egyptian Journal of Aquatic Biology & Fisheries . 21(2), 67-78.

Mendes, B., Fonseca, P. and Campos, A. (2004). Weight-length relationships for 46 fish species of the Portuguese west coast. J. of Applied Icht . 20: 355- 361.

M'hetli, M., Ben Khemis, I., Hamza, N., Turki, B., and Turki, O. (2011). Allometric growth and reproductive biology traits of pikeperch Sander lucioperca at the southern edge of its range. Journal of fish biology , 78 (2), 567-579.

Mitcheson, D., Sadovy, Y., and Liu, M. (2008). Functional hermaphroditism in teleosts. Fish and Fisheries , 9(1), 1-43.

Mohammad, A., and Pathak, J. K. (2010). Assessment of fecundity and gonadosomatic index of commercially important fish, Labeo rohita from Ramganga River. International Journal of Pharma and Bio Sciences , 1(3).

Mohammadi-Darestani, M., Mousavi-Sabet, H., Vatandoust, S., and Ahmadnejad, M. (2016). Age, growth and reproduction of the Iranian goby, Ponticola iranicus (Perciformes: Gobiidae) from the southern Caspian Sea basin. Journal of ichthyology , 56 (4), 578-587.

Mohan, M. (2005). Spawning biology of snow trout, Schizothorax richardsonii (gray) from River Gaula (Kumaon, Himalayas). Indian Journal of Fisheries , 52 (4), 451- 457.

Mojekwu, T. O., and Anumudu, C. I. (2015). Advanced techniques for morphometric analysis in fish. Journal of Aquaculture Research & Development , 6(8), 1.

167

Morato, T., Afonso, P., Lourinho, P., Barreiros, J. P., Santos, R. S., and Nash, R. D. M. (2001). Length–weight relationships for 21 coastal fish species of the Azores, north-eastern Atlantic. Fisheries Research , 50(3), 297-302.

Morris, A. D. (2005). Length-weight Relationships for Twenty Marine Fishes of Texas. Texas Parks and Wildlife Department, Coastal Fisheries Division. Management Data Series No. 227

Mortuza, M. G., and Rahman, T. (2006). Length-weight relationship, condition factor and sex-ratio of freshwater fish, Rhinomugil corsula (Hamilton) (Mugiliformes: Mugilidae) from Rajshahi, Bangladesh. Journal of Bio-science , 14 , 139-141.

Mortuza, M., and Al-Misned, F. A. (2015). Length–Weight Relationships of Twelve Fishes from the River Padma near Rajshahi City, Bangladesh. Fisheries and Aquaculture Journal . 6:1 http://dx.doi.org/10.4172/2150-3508.1000113

Mozsár, A., Boros, G., Sály, P., Antal, L., and Nagy, S. A. (2015). Relationship between Fulton's condition factor and proximate body composition in three freshwater fish species. Journal of Applied Ichthyology , 31(2), 315-320.

Muncaster, S., Andersson, E., Kjesbu, O. S., Taranger, G. L., Skiftesvik, A. B., and Norberg, B. (2010). The reproductive cycle of female Ballan wrasse Labrus bergylta in high latitude, temperate waters. Journal of Fish Biology , 77 (3), 494- 511.

Muñoz, M., Dimitriadis, C., Casadevall, M., Vila, S., Delgado, E., Lloret, J., and Saborido ‐ Rey, F. (2010). Female reproductive biology of the bluemouth Helicolenus dactylopterus dactylopterus: spawning and fecundity. Journal of Fish Biology , 77 (10), 2423-2442.

Murata, O., Kato, K., Ishitani, Y., Nasu, T., Miyashita, S., Yamamoto, S., and Kumai, H. (1997). Gonadal Maturation of Pagrus major× Acanthopagrus schlegeliand Pagrus major× Sparus sarba Sea Bream Hybrids. Aquaculture Science , 45 (1), 75-80.

Murta, A. G. (2000). Morphological variation of horse mackerel ( Trachurus trachurus ) in the Iberian and North African Atlantic: implications for stock identification. ICES Journal of Marine Science , 57 (4), 1240-1248.

168

Musick, J.A. (1999). Ecology and conservation of long-lived marine animals. In: Musick, J.A., (ed.). Life in the Slow Lane: Ecology and Conservation of Long-Lived Marine Animals. Amer. Fish. Soc. Symp . 23, Bethesda, MD, pp. 1–10.

Naeem, M. andSalam, A. (2005) Morphometric Study of Fresh Water Bighead Carp Aristichthys nobilis From Pakistan In Relation To Body Size. Pak. J. Biol. Sci. 8 (5): 759-762.

Naeem, M., Salam, A., Ashraf, M., Khalid, M., and Ishtiaq, A. (2011). External morphometric study of hatchery reared mahseer (Tor putitora) in relation to body size and condition factor. African Journal of Biotechnology , 10 (36), 7071-7077.

Naga, W. M. A., and Allam, S. M. (1999). Trace metal concentration in the tissues of Tilapia zillii gerv exposed to waste water discharge of an Egyptian copper works. Pakistan Journal of Marine Sciences (Pakistan) . 8(2), 115-122.

Nakamura, M. (2013). Morphological and physiological studies on gonadal sex differentiation in teleost fish. Aqua-BioScience Monographs, 6(1) 1-47.

Nandikeswari, R., and Anandan, V. (2013). Analysis on gonadosomatic index and fecundity of Terapon puta from Nallavadu coast Pondicherry. Int. J. Sci. Res. Pub. ISSN , 3(2), 2250-3153.

Napazakov, V. V. (2008). Feeding interactions and diet of carnivorous fishes in the Shelikhov Bay of the Sea of Okhotsk. Russian Journal of Marine Biology , 34 (7), 452-460.

Nasir, M. F., Naeem, M., and Naeem, A. (2017).Length-weight and Morphometric Relationship of Farmed Male and Female Clarias batrachus from Pakistan. BIOLOGIA (PAKISTAN) , 43.

Natarajan, L.V. and Jhingran, A.G. (1961). Index of preponderance a method of grading the food elements in the stomach analysis of fishes. Indian J. Fish. 8(1) 54-9.

National Institutes of Health. (2017). U.S. Department of Health and Human Services. Office of Dietary Supplements. https://ods.od.nih.gov/factsheets/list-all . Retrieved on August 19, 2017.

National Policy and Strategy for Fisheries and Aquaculture Development in Pakistan. Ministry of food, Agriculture and Livestock: Government of Pakistan (2006).

169

Nazir, K., Yongtong, M., Hussain, K., Kalhoro, M. A., Kartika, S., and Mohsin, M. (2016). A Study on the Assessment of Fisheries Resources in Pakistan and its Potential to Support Marine Economy. Indian Journal of Geo-Marine Sciences, 45(9), 1181- 1187.

Nazir, K., Yongtong, M., Kalhoro, M. A., Memon, K. H., Mohsin, M., and Kartika, S. (2015). A preliminary study on fisheries economy of Pakistan: plan of actions for fisheries management in Pakistan. Canadian Journal of Basic and Applied Sciences , 3(01), 7-17.

Nichol, D.G., Acuna, E.I. (2001). Annual and batch fecundities of yellowfin sole, Limanda aspera , in the eastern Bering Sea. Fish .Bull. 99, 108–122.

Nikolskii, G.V. (1963). The Ecology of Fishes, New York: Academic Press.

Nikolsky, G. V. (1969). Theory of the Fish Population Dynamics as the Biological Background for Rational Exploitation and Management of Fisheries Resources. Oliver and Boyd: Edinburgh . 322 p.

Nip, T. H., Ho, W. Y., and Wong, C. K. (2003). Feeding ecology of larval and juvenile black seabream ( Acanthopagrus schlegeli ) and Japanese seaperch ( Lateolabrax japonicus ) in Tolo Harbour, Hong Kong. Environmental Biology of Fishes , 66 (2), 197-209.

Norriss, J. V., Tregonning, J. E., Lenanton, R. C. J. and Sarre, G. A. (2002). Biological synopsis of the black bream Acanthopagrus butcheri (Munro) (Teleostei: Sparidae) in Western Australia with reference to information from other states. Fisheries Research Report no. 93, Department of Fisheries, Western Australia, 48p.

Offem, B.O., Samsons Y.A. and Omoniyi, I.T. (2008). Diet, size and reproductive biology of the silver catfish, Chrysichthys nigrodigitatus (Siluformes: Bagridae) in the Cross River, Nigeria. Revista de biología tropical , 56 (4), 1785-1799.

Olagbemide, P.T. (2010). Length frequency distribution and length-weight relationship of Schilbe mystus from Lekki Lagoon in Lagos, Nigeria. Journal of agricultural and veterinary sciences , 2, 63-69.

Oliveira, M. R., Carvalho, M. M., Silva, N. B., Yamamoto, M. E., and Chellappa, S. (2015). Reproductive aspects of the flyingfish, Hirundichthys affinis from the

170

Northeastern coastal waters of Brazil. Brazilian Journal of Biology , 75 (1), 198- 207.

O'Reilly, K. M., and Horn, M. H. (2004). Phenotypic variation among populations of Atherinops affinis (Atherinopsidae) with insights from a geometric morphometric analysis. Journal of Fish Biology , 64 (4), 1117-1135.

Pajuelo, J.G., Socorro, J., Gonzólez, J.A., Lorenzo, J.M., Pérez-Peñalvo, J.A., Martinz, I. and Hernandez-Cruz, M. (2006). Life history of the red-banded seabream Pagrus auriga (Sparidae) from the coasts of the Canarian archipelago. J. Appl. Ichthyol . 22(5), 430–436.

Pakistan: Sindh Coastal and Inland Community Development Project. (2005). Interim report, Volume II. ANZDEC Limited, New Zealand in cooperation with Resource Monitoring and Development Group, Pakistan and SEBCON (Pvt) Limited, Pakistan.

Pallaoro, A., Santic, M. and Jardas, I., (2004). Diet composition of young-of-the-year saddled bream, Obladame lanura (Linnaeus, 1758) from the eastern central Adriatic Sea. Journal of Applied Ichthyology . 20, 228–230.

Panhwar, S. K., Siddiqui, G., and Ayub, Z. (2011). Reproductive pattern and some biological features of anadromous fish Tenualosa ilisha (family: clupeidae) from Pakistan.

Panhwar, S. K., Siddiqui, G., and Ayub, Z. (2012). Gonads annual development of kelee shad, Hilsa kelee (Cuvier, 1829) from the coastal waters of Pakistan and its spawning ecology. Russian Journal of Marine Biology , 38 (1), 79-87.

Parent, S. and Schriml, L.M. (1995). A model for the determination of fish species at risk based upon life-history traits and ecological data. Can. J. Fish. Aquat. Sci . 52, 1768–1781.

Patra, K.P., Das, S. and Sahu, S. (2000). Seasonal fluctuation of trace metals in P. Monodon of Ganjam, East coast of India. Indian J fish . 47(3):271-274.

Pauly, D. (1984). Length-converted catch curves. A powerful tool for fisheries research in the tropics. (Part II). ICLARM Fishbyte 2(1), 17–19.

171

Pazhayamadom, D. G., Chakraborty, S. K., Jaiswar, A. K., Sudheesan, D., Sajina, A. M., and Jahageerdar, S. (2015). Stock structure analysis of ‘Bombay duck’ (Harpadon nehereus Hamilton, 1822) along the Indian coast using truss network morphometrics. Journal of Applied Ichthyology , 31 (1), 37-44.

Peacock, M. (2010). Calcium metabolism in health and disease. Clinical Journal of the American Society of Nephrology 5: S23 – S30.

Pet, J. S., Wijsman, J. W. M., Mous, P. J., and Machiels, M. A. M. (1995). Characteristics of a Sri Lankan reservoir fishery and consequences for the estimation of annual yield. Fisheries research , 24 (1), 9-33.

Petrakis, G., and Stergiou, K. I. (1995). Weight-length relationships for 33 fish species in Greek waters. Fisheries research , 21(3-4), 465-469.

Pillay, S. R. and Rao, K.V. (1960). Observations on the biology and fishery of hilsa, Hilsa ilisha (Ham) on river Godavari, Proc. Indo-Pacif. Fish.Cum . 10(2): 37- 61.

Platell, M. E., Ang, H. P., Hesp, S. A., and Potter, I. C. (2007). Comparisons between the influences of habitat, body size and season on the dietary composition of the sparid Acanthopagrus latus in a large marine embayment. Estuarine, Coastal and Shelf Science , 72 (4), 626-634.

Plaza, G., Sakaji, H., Honda, H., Hirota, Y., and Nashida, K. (2007). Spawning pattern and type of fecundity in relation to ovarian allometry in the round herring Etrumeus teres . Marine Biology , 152 (5), 1051-1064.

Pohl, H.R., Wheeler, J.S. and Murray, H. E. (2013). Sodium and potassium in health and disease. Met Ions Life Science 13:29-47.

Polis, G.A., Sears, L.W., Huxel, D.R. and Strong, J.M. (2000). When is a trophic cascade a trophic cascade? Trends Ecol. Evol . 15, 473–475.

Pollock, B. R., and Williams, M. J. (1983). An assessment of the angling fishery for yellowfin bream, Acanthopagrus australis (Günther), in Moreton Bay, Australia. Journal of Fish Biology , 22 (2), 125-132.

Poltev, Y. N., and Stominok, D. Y. (2008). Feeding habits the Pacific cod Gadus macrocephalus in oceanic waters of the Northern Kuril Islands and Southeast Kamchatka. Russian Journal of Marine Biology , 34 (5), 316-324.

172

Pompei, L., Giannetto, D., and Lorenzoni, M. (2014). Feeding ecology of Padogobius nigricans (Canestrini, 1867) and P. bonelli (Bonaparte, 1846) in Aggia River (Umbria, Italy) and their diet overlap. Hydrobiologia , 740 (1), 101-113.

Pravina, P., Sayaji, D. and Avinash, M. (2013). Calcium and its role in human body, review article. International journal of Research in Pharmaceutical and Biomedical Sciences 4(2): 659 – 668.

Randall, J.E. (1995). Coastal Fishes of Oman. University of Hawaii Press, Honolulu, Hawaii, 227p.

Reid, G. M. (1961). Stomach content analysis of troll-caught king and coho salmon, Southeastern Alaska, 1957-58 (No. 379). US Department of Interior, Fish and Wildlife Service.

Rejomon, G., Nair, M., and Joseph, T. (2010). Trace metal dynamics in fishes from the southwest coast of India. Environmental Monitoring and Assessment , 167 (1-4), 243-255.

Reynolds, J. D. (1974). Biology of the small pelagic fishes in the New Volta Lake in Ghana. Part III: Sex and reproduction. Hydrobiologia , 45 (4), 489-508.

Rickman, S.J., Dulvy, N.K., Jennings, S., Reynolds, J.D. (2000). Recruitment variation related to fecundity in marine fishes. Can. J. Fish. Aquat. Sci . 57, 116–124.

Rizkalla, S.I. (1994). A comparative study on the morphometric characters of fishes belonging to family: Centracanthidae in the Egyptian Mediterranean waters. J. KAU: Mar. Sci. ; 7:55-261.

Roa, R., Ernst, B., Tapia, F. (1999). Estimation of size at sexual maturity: an evaluation of analytical and resampling procedures. Fish. Bull . 97, 570–580.

Rocha, F., and Gadig, O. B. F. (2013). Reproductive biology of the guitarfish Rhinobatos percellens (Chondrichthyes, Rhinobatidae) from the São Paulo Coast, Brazil, western South Atlantic Ocean. Journal of fish biology , 82 (1), 306-317.

Roubal, F. R. (1994). Observations on the eggs and-fecundity of dactylogyrid and diplectanid monogeneans from the Australian marine sparid fish, Acanthopagrus australis . Folia Parasitologica , 41 , 220-222.

173

Roy, P. K. and Hossain, M. A. (2006). The fecundity and sex ratio of Mystus cavasius (Hamilton) (Cypriniformes: Bagridae). The Journal of Life and Earth Science , 1(2), 65-66.

Saeed, A. R., Moharram, S. G., and Al-Abbasi, F. A. (2016). A comparative gametogenesis and biochemical differentiation of goatfish (Family: Mullidae) from the Red Sea. Russian Journal of Marine Biology , 42 (1), 42-50.

Saei-Dehkordi, S. S., and Fallah, A. A. (2011). Determination of copper, lead, cadmium and zinc content in commercially valuable fish species from the Persian Gulf using derivative potentiometric stripping analysis. Microchemical Journal , 98 (1), 156- 162.

Safahieh, A., Babadi, S., Nabavi, S. M. B., Ronagh, M. T., and Ghanemi, K. (2013). Assessment of mercury intake through consumption of yellowfin seabream (Acanthopagrus latus ) from Musa Estuary. Journal of Life Sciences and Technologies Vol , 1(2).

Safi, A., Khan, A., Hashmi, M. U. A. and Khan Z. M. (2014). Length-weight relationship and condition factor of stripped piggy fish, Pomadasys stridens (Forsskäl, 1775) from Karachi coast, Pakistan. J. Entomo. & Zool. Studies . 2(5): 25-30.

Safi, A., Khan, M. A., and Khan, M. Z. (2014). Study of some morphometric and meristic characters of striped piggy fish, Pomadasys stridens (Forsskal, 1775) from Karachi Coast, Pakistan. The Journal of ZoologicalStudies , 1, 1-6.

Saikia, A. K. (2012). Morphometric and biometric index study of Channa punctatus (Bloch) from paddy field of sivsagar District, Assam. Journal of Biological and Chemical Science , 29 (1), 37-43.

Salam, A., and Naeem, M. (2004). Some morphometric studies of common carp Cyprinus carpio in relation to body size, from Islamabad, Pakistan. Sindh. Univ. Res. J. (Sci. Ser) , 36 , 21-48.

Salamat, N., Soleimani, Z., Safahieh, A., Savari, A., and Ronagh, M. T. (2013). Using histopathological changes as a biomarker to trace contamination loading of Musa Creeks (Persian Gulf). Toxicologic pathology , 41 (6), 913-920.

174

Saleem, M. (2002). Study of Heavy Metal Pollution Level and Impact on the Fauna, and Flora of the Karachi and Gawadar Coast. National institute of oceanography, Final project report , (50022801), 32.

Samoilys, M. A., Osuka, K., Maina, G. W., and Obura, D. O. (2017). Artisanal fisheries on Kenya’s coral reefs: Decadal trends reveal management needs. Fisheries research , 186, 177-191.

Santos, M. N., Monteiro, C. C., and Erzini, K. (1995). Aspects of the biology and gillnet selectivity of the axillary seabream ( Pagellus acarne , Risso) and common pandora (Pagellus erythrinus , Linnaeus) from the Algarve (south Portugal). Fisheries Research , 23 (3-4), 223-236.

Santos, M.B., Clarke, M.R. and Pierce, G.J. (2001). Assessing the importance of cephalopods in the diets of marine mammals and other top predators: problems and solutions. Fish Res 52:1 21−139.

Sarker, P. K., Pal, H. K., Rahman, M. M., and Rahman, M. M. (2002). Observation on the fecundity and gonado-somatic index of Mystus gulio in brackishwater of Bangladesh. Online J. Biol. Sci , 2(4), 235-237.

Sarre, G. A., and Potter, I. C. (1999). Comparisons between the reproductive biology of black bream Acanthopagrus butcheri (Teleostei: Sparidae) in four estuaries with widely differing characteristics. International Journal of Salt Lake Research , 8(3), 179-210.

Saud, A. J. (2011). Weight-length Relationships, Gonadosomatic Indeces, Sex Ratios and Relative eight of the Omani-Indian Oil sardine, Sardinella longiceps (Valenciennes1847) from Al-Seeb Area; Sultanate of Oman. Advance Journal of Food Science and Technology , 3(4), 238-244.

Shilta, M. T., Suresh Babu, P. P., Asokan, P. K., Vinod, K., Imelda, J., Sawant, P. B., and Chadha, N. K. (2018). Gonadal Assessment of Picnic Sea Bream Acanthopagrus berda (Forsskål 1775), a Potential Aquaculture Candidate for Indian Waters. Asian Fisheries Science , 31 , 45-60.

175

Shriadah, M.A. and Emara, H.I. (1991). The distribution of chromium, copper, cadmium and lead in areas of multi-polluting factors of Alexandria. Proceeding of Symposium of Marine Chemistry In the Arab Region, Suez, April, 39–50.

Siddiqui, P. J., Amir, S. A. and Masroor, R. (2014). The sparid fishes of Pakistan, with new distribution records. Zootaxa. http://dx.doi.org/10.11646/zootaxa.0000.0.0

Simopolpoulos, A.P., (1997). Seafood from producer to consumer, natural aspects of the fish. In: Lutten, J.B., Borrensen, T., Oehlenschla ¨ger, J. (Eds.), Seafood from producer to consumer, integrated approach to quality, 38. Elsevier, Amsterdam, The Netherlands , pp. 587–607.

Singla, R. B. (2016). Morphometric alterations in exotic freshwater fish, Ctenopharyngodon idella (Cuv. and Val.) upon exposure to endosulfan. Int J Fish Aquat Stud , 4(3), 590-593.

SMEDA (2002). Small and Medium Enterprise Development Authority. Government of Pakistan.

SMEDA (2005). Small and Medium Enterprise Development Authority. Government of Pakistan.

Sourinejad, I., Nikkhah Khaje Ataei, S., Kamrani, E., and Ghodrati Shojaei, M. (2015). Feeding habits of yellowfin seabream, Acanthopagrus latus in the northern region of the Persian Gulf. Caspian Journal of Environmental Sciences , 13 (1), 31-39.

Sparre, P. (1998). Introduction to tropical fish stock assessment. Part 1. Manual. FAO Fish. Tech. Paper. , 306, 1-407.

Stearns, SC. (1992). The evolution of Life histories. Oxford, UK: University Press, Oxford , 250p.

Stoner, A. and Livingston, R. (1984). Ontogenetic patterns in diet and feeding morphology in sympatric sparid fishes from seagrass meadows. Copeia , pp 174–187.

Strauss, R. E., and Bookstein, F. L. (1982). The truss: body form reconstructions in morphometrics. Systematic Biology , 31 (2), 113-135.

176

Sun, C. L., Yeh, S. Z., Chang, Y. J., Chang, H. Y., and Chu, S. L. (2013). Reproductive biology of female bigeye tuna Thunnus obesus in the western Pacific Ocean. Journal of fish biology , 83 (2), 250-271.

Sun, L. T., and Jeng, S. S. (1998). Comparative zinc concentrations in tissues of common carp and other aquatic organisms. Zoological Studies , 37 (3), 184-190.

Surya, S., Saravanan, R., Nazar, A. A., Padua, S., Roul, S. K., and Ambarish, G. P. (2016). Morphometry and Length-Weight Relationship of Uranoscopus marmoratus Cuvier, 1829 (Family: Uranoscopidae) from Palk Bay, India. International Research Journal of Biological Sciences , 5(11), 1-10.

Swynnerton, G.H. and Worthington, E.B. (1940). Notes on the food of fish in Hawes water (West Morland). J Anim Ecol . 9:183–187.

Tancioni, L., Mariani, S., Maccaroni, A., Mariani, A., Massa, F., Scardi, M., and Cataudella, S. (2003). Locality-specific variation in the feeding of Sparus aurata L.: evidence from two Mediterranean lagoon systems. Estuarine, Coastal and Shelf Science , 57 (3), 469-474.

Tandon KK, Johal MS, Bala S. (1993). Morphometry of Cirrhinus reba (Hamilton) from Kanjli wetland, Punjab, India. Res Bull Punjab Univ Sci 43(1-4), 73-78.

Tariq, J., Ashraf, M., Jaffar, M., and Masud, K. (1998). Selected trace metal concentration in seven fish species from the Arabian Sea, Pakistan. Journal-Chemical Society of Pakistan , 20 , 249-250.

Tariq, J., JaffarM.and Moazzam,M. (1993). Heavy metal concentration in fish, shrimp,seaweed,sediment and water from the Arabian Sea, Pakistan. Mar. Pollut. Bull ., 26: 644–7.

Toor, H. S. (1964). Biology and fishery of the pig-face bream, Lethrinus lentian Lacepede II. Maturation and spawning. Indian Journal of Fisheries , 11 (2), 581-596.

Turan, C. (2004). Stock identification of Mediterranean horse mackerel ( Trachurus mediterraneus ) using morphometric and meristic characters. ICES Journal of Marine Science , 61 (5), 774-781.

177

Turan, C., Yalçin, S., Turan, F., Okur, E., and Akyurt, I. (2005). Morphometric comparisons of African catfish, Clarias gariepinus , populations in Turkey. Folia Zoologica , 54 (1/2), 165.

Tyler, C. R., and Sumpter, J. P. (1996). Oocyte growth and development in teleosts. Reviews in fish biology and fisheries , 6(3), 287-318.

Tyokumbur, E. (2016). Bioaccumulation Of Some Metals In The Fish Sarotherodon Galilaeus Caught From Alaro Stream In Ibadan. International Journal of Pure and Applied Zoology , 4(2) 186-188.

Uiblein, F. (1995). Morphological variability between populations of Neobythites stefanovi (Pisces: Ophidiidae) from the deep Red Sea and the Gulf of Aden. Marine Ecology Progress Series , 23-29.

Ujjania, N. C., and Kohli, M. S. (2011). Landmark-based morphometric analysis for selected species of Indian major carp (Catla catla, Ham. 1822). Int J Food Agric Vet Sci , 1, 64-74.

Usero, J., Izquierdo, C., Morillo, J. and Gracia, I. (2003). Heavy metals in fish ( Solea vulgaris, Anguilla anguilla and Liza aurata ) from salt marshes on the southern Atlantic coast of Spain. Environ Int 29:949–956.

Vahabnezhad, A., Kaymaram, F., Taghavi Motlagh, S. A., Valinassab, T., and Fatemi, S. M. R. (2016). The reproductive biology and feeding habits of yellow fin seabream, Acanthopagrus latus (Houttuyn, 1782), in the Northern Persian Gulf. Iranian Journal of Fisheries Sciences , 15 (1), 16-30.

Vatandoust, S., Abdoli, A., Anvarifar, H., and Mousavi-Sabet, H. (2014). Morphometric and meristic characteristics and morphological fario (Pisces: Salmonidae) along the southern Caspian Sea basin. European Journal of Zoological Research , 3(2), 56-65.

Vormann, J. (2003). Magnesium: nutrition and metabolism. Molecular Aspects of Medicine 24: 27–37.

Wallace, R. K. (1981). An assessment of diet-overlap indexes. Transactions of the American Fisheries Society 110: 72–76.

178

Wallace, R.A. and K. Selman. (1989). Cellular and dynamic aspects of oocyte growth in teleosts. Am. Zool . 21: 325–343.

Watson, R., & Pauly, D. (2001). Systematic distortions in world fisheries catch trends. Nature , 414, 534-536.

Weatherley, A.H. and Gill, H.S. (1987), “The biology of fish growth”, London. pp. 443.

WHO (1996). Health criteria other supporting information. In: Guidelines for Drinking Water Quality, vol. 2, 2nd ed., pp. 31-388, Geneva.

Winiarska-Mieczan, A. (2014). Content of Na, K, Ca and Mg in complementary infant food. J. Elem ., 19(2): 587-596. DOI: 10.5601/jelem.2014.19.2.648

Yakubu, A., and Okunsebor, S. A. (2011). Morphometric differentiation of two Nigerian fish species ( Oreochromis niloticus and Lates niloticus ) using principal components and discriminant analysis. International Journal of Morphology , 29 (4), 1429-1434.

Yankson, K., and Azumah, E. G. S. (1993). Aspects of reproduction and diet of the long ‐ finned herring, Ilisha africana , off Cape Coast, Ghana. Journal of fish biology , 42 (5), 813-815.

Yesser, A. T., and AL-Taee, M. A. J. (2013). Determinatio n of some toxic trace elements of fresh, frozen and canned fish species. Basrah Journal of Veterinary Research. 12 (2), 139-148.

Yılmaz, A. B., Sangün, M. K., Ya ğlıo ğlu, D., and Turan, C. (2010). Metals (major, essential to non-essential) composition of the different tissues of three demersal fish species from Iskenderun Bay, Turkey. Food chemistry , 123(2), 410-415.

Yilmaz, S., Yazicioglu, O., Erbasaran, M., Esen, S., Zengin, M. and Polat, N. (2012). Length-weight relationship and relative condition factor of white bream, Blicca bjoerkna (L., 1758), from Lake Ladik, Turkey. J. Black Sea/ Mediterranean Environment . 18 (3): 380 – 387.

Yu-sheng, Q., Zheng-yin, W., La-tie, J. and Shi-hua, T. (2010). Cadmium uptake by paddy rice and soil available Cd under water flooding as affected by nitrogen fertilizer. ICBBE 4th International Conference. 1, 1–5.

179

Zakeri, M., Savari, A., Kochanian, P., and Haghi, M. (2010). Effects of artificial diets on biological performances of Acanthopagrus latus broodstock in the Persian Gulf. Journal of the Persian Gulf , 1(2), 1-10.

Zar, J. H. (1999). Biostatistical Analysis. 4th edn. Prentice-Hall, Upper Saddle River, NJ. 931 pp.

Zarbalieva, T.S. (1973). Age and Seasonal Changes in the Diet of Young Sturgeon at the Western Coast of the Middle Caspian Sea, Novoe v rybokhozyaistvennykh issledovaniyakh Azerbaidzhana, ( Advances in Azerbaijan Fisheries Researches), Baku. pp. 63–81.

Zhong, J., Yu M., Liu L., Chen Y., Hu R. and Gong, W. (2006). Study on the dietary nutrition intake level in Zhejiang Province. Dis Surveillance ; 21:670–672.

180